The Irish
Sports Monitor
First Annual Report, 2007
Pete Lunn, Richard Layte
& Dorothy Watson
The Economic and
Social Research Institute (ESRI)
Acknowledgements
The authors would like to thank The Irish Sports Council for its support and commitment to the Irish Sports
Monitor (ISM). We are also grateful to a range of international researchers who contributed materials and advice
to the development of the ISM, including: Jon Best (Sport Scotland), Dr. Fiona Bull (Loughborough University,
UK), Richard Myles (York University, Canada) and Dr. Adrian Bauman (University of Sydney, Australia).
We would also like to thank the interviewing team of the Economic and Social Research Institute (ESRI) for their
hard work in collecting the data and Dr. Joanne Banks for helpful comments on an earlier draft of this report.
Contents
Highlights
4
Part One: Introduction
6
1. Background and Aims of the ISM
7
Part Two: Physical Participation
10
2. How Active Are We?
3. FITT Analysis
4. Comparison of Social Groups
5. Comparison by County/Council
6. Relative Popularity of Sports
7. Walking
8. International Comparison
11
14
18
23
25
29
32
Part Three: Social Participation
34
9. Volunteering
10. Club Membership
11. Attendance
35
39
42
Part Four: Conclusions
45
12. Contribution of the 2007 ISM
46
References
49
Appendices
50
Appendix A - ISM Technical Report
Appendix B Questionnaire
51
53
Highlights*
Physical Participation
How Active are We
• In 2007, 24% of the adult population could be classified as “Highly Active”, 28% “Fairly Active”, 30% “Just
Active” and 18% “Sedentary”
• 33% played sport for at least 20 minutes during the previous 7 days
• 58% went for a recreational walk of at least 20 minutes during the previous 7 days
FITT Analysis
• There was variation by season: fewer people played sport towards the end of the year
• 68% of participants played more than once a week, 69% with high effort
• 62% played their sport in a non-organised setting, with family, friends or alone
Comparison of Social Groups
• People with high educational attainment, men, younger people and those on high incomes were much more
likely to play sport and much less likely to be sedentary
• The estimated impact of income on the likelihood of playing sport was even higher than previously reported
• Non-Irish nationals from outside the EU and the English-speaking countries were approximately half as
likely to play sport as Irish nationals
Comparison by County/Council
• Comparing the highest performing areas with the lowest performing areas, more than two-and-a-half times
as many people played sport in the previous 7 days
• Controlling for population profile, Dún Laoghaire-Rathdown and Mayo recorded high participation
• Controlling for population profile, Dublin City, Limerick, Kildare, Offaly, Leitrim and Westmeath recorded
low participation
Relative Popularity of Sports
• Personal exercise activities (going to the gym, fitness classes, exercise machines etc.) are now the most
popular sport and exercise activity in Ireland, followed by swimming
• Soccer is by far the most popular team sport, but ranks poorly among women relative to other sports
• Combining volunteering, membership and attendance, Gaelic games remain the leading sports for social
participation, but there are now more gym members than GAA members
Walking
• 14% of the population went for a recreational walk every day the previous week, while 42% did not take a
walk at all
• Women walk more than men and seem to be a strong influence, since men in couples walk much more than
single men
• 40% walk regularly for transport, although the figure is much lower in rural locations
International Comparison
• Active participation in sport and exercise in Ireland is broadly in line with participation in other developed countries
• Participation rates are nevertheless far behind those of the best performing countries, which are the
Scandinavian nations and English-speaking Commonwealth nations
• Participation rates are clearly ahead of the worst performers, which tend to be Southern European nations
Social Participation
Volunteering
• 8% of adults had volunteered for sport-related activity in the previous 7 days, equivalent to 280,000
volunteers
• Disabled people who said they could not actively participate in sport were more likely to be involved as
volunteers than those without a disability
• The average time devoted to volunteering in the previous 7 days was two hours, but women and, especially,
men over 65 years of age devoted very much more time
Club membership
• 32% of adults are members of sports clubs
• Disabled people over age 45 who said they could not actively participate in sport were more likely to be club
members than those without a disability
• Club membership was strongly related to high income and educational attainment
Attendance
• 17% of adults had attended a sporting event in the previous 7 days
• Men were more likely to attend than women, but women with children under 18 were particularly likely to
attend and more likely to attend two or three events
• Attendance was strongly affected by income and social class
*All figures are based on a representative sample of just under 10,000 adults aged 16 and over interviewed
regularly throughout 2007
Part One:
Introduction
1. Background and Aims of the ISM
The Irish Sports Monitor (ISM) has been established as an ongoing survey of participation in sport in Ireland. This
is the first annual report of the ISM, based on the data collected in 2007. The project involves the collection of over
9,200 questionnaire responses by telephone, from a representative sample of the Irish public aged 16 and over, and
the monitoring and analysis of the resulting patterns and trends relating to participation in Irish sport. Although
some sporting organisations operate on an all-Ireland basis, the ISM covers only residents of the Irish state.
Aims of the ISM
The primary aim is to measure participation levels with sufficient accuracy that levels and trends can be
monitored over a number of years. This first annual report, for 2007, therefore acts as a baseline against which
participation in future years can be assessed. In addition to this fundamental aim, the ISM has the capacity to
further expand the available research on Irish sport, with a view to assisting both the policy making process and
all those involved in the promotion and development of sport in Ireland.
The findings presented here should be viewed in the context of ongoing research that has made extensive use
of previous surveys, most notably the Survey of Sport and Physical Exercise (SSPE) of 2003, the Survey of
Schoolchildren’s Sport carried out in 2004, and the Quarterly National Household Survey (QNHS) Module
on Sport and Social Capital, conducted by the Central Statistics Office in 2006. Where possible, we have cross
referenced the results from the ISM with these previous surveys, although in some instances differences in
methodology can produce quite large disparities (see especially the discussion on rates of walking in Chapter 2).
There is now a substantial body of research based on these nationally representative surveys (see Lunn, 2007b,
for overview). Fahey, Layte and Gannon (2004) were the first to examine levels of participation using a largescale national survey. Delaney and Fahey (2005) extended this analysis to cover the social and economic benefits
of sport. Fahey, Delaney and Gannon (2005) produced extensive findings specific to schoolchildren’s sport.
Lunn (2007a) examined the strong relationship between participation in sport and social disadvantage. Lastly,
Lunn and Layte (2008) used the SSPE to reconstruct the recent history of Irish sport and thus to reveal trends in
participation over recent generations and across the life-course.
In addition to providing a baseline for reference in future years, this present report adds findings to this body of
work, based on the largest sample of micro-data analysed to date.
Questionnaire Development
The design of the questionnaire for the ISM is based on careful examination of similar ongoing participation
surveys of sport and physical activity conducted in other countries. Questionnaires were collected and
scrutinised from England, Scotland, Wales, Canada, Australia and New Zealand. We also consulted with
researchers involved in their development and examined published analyses based on the data generated. In
addition, previous Irish surveys of sport and physical activity were considered as possible templates for the ISM.
There would have been advantages associated with using a pre-existing questionnaire, including the ability to
compare initial results with some previous findings. Some of these pre-existing questionnaires have also been
tested for reliability and validity. It was decided, however, to develop an entirely new survey instrument for the
ISM. This decision was taken for two reasons.
First, a new questionnaire could be designed specifically to measure participation in ‘sport’ as defined in Irish policy.
The appropriate definition of sporting activity is provided in the Sports Council Act of 1999 (see below). The Irish
Sports Council has responsibility for the promotion and development of a specific range of sports that fall under this
definition. The Council also has a strategic commitment to raise the level of participation in ‘sport’, as defined. Preexisting international questionnaires were not designed with this specific range of activities in mind, and hence their
usefulness for monitoring activity in the Irish policy context would have been limited. The primary purpose of the
ISM is to measure and monitor participation in a particular policy context and so a new instrument was preferable.
Second, a new questionnaire could improve accuracy relative to previous Irish surveys by asking respondents to
recall their sport and exercise activities during only the previous 7 days. The questionnaires previously employed
in Ireland used a ‘reference period’ (the period of time over which respondents are asked to recall their activities)
of 12 months. Such a long reference period makes sense for one-off cross-sectional surveys, as it obtains more
information about sporting activity per respondent. But when the primary aim is to improve the sensitivity of
comparisons over time, a reference period of 12 months will introduce more error, since it is harder to recall
activity accurately over the longer period. In order to make comparisons across years, participation levels need to
be measured with the highest possible accuracy, so the 7-day reference period was chosen.
The questionnaire was piloted in late 2006 and went “live” in the first quarter of 2007. The telephone interviews
were conducted by the ESRI Survey Unit. A full description of the survey methodology is given in Appendix A
and the questionnaire is provided in Appendix B. The sample-size of the ISM for 2007 is 9,796 usable responses
collected from a representative sample of individuals resident in Ireland and aged 16 and over. Details on
weighting, response rates and other technical information are also provided in Appendix A.
Definition of ‘Sport’
The definition of sport adopted in the context of Irish sports policy is derived from the Council of Europe’s 1992
European Sports Charter and was adapted and established in the Irish context through the Irish Sports Council
Act of 1999. It distinguishes between competitive and recreational sport:
‘‘competitive sport’’ means all forms of physical activity which, through organised participation, aim at
expressing or improving physical fitness and at obtaining improved results in competition at all levels;
‘‘recreational sport’’ means all forms of physical activity which, through casual or regular participation, aim at
expressing or improving physical fitness and mental well-being and at forming social relationships;
(Irish Sports Council Act, 1999, Part 1, Sect. 2(1))
Thus, the defintion of sport with respect to Irish policy is very broad. It encompasses not only traditional
competitive sport, but also exercise activities such as walking and cycling, plus a range of other exercise activities
aimed at improving physical fitness. When we refer to ‘grassroots’ sport throughout this report, we are referring
to both competitive and recreational sport played by the population at large.
Increasing Participation
Part 1, Section 6(1) of the same act, lists the statutory functions of the Council, of which two are particularly
relevant in the present context:
(a) to encourage the promotion, development and co-ordination of competitive sport and the achievement of
excellence in competitive sport,
(b) to develop strategies for increasing participation in recreational sport and to co-ordinate their
implementation by all bodies (including public authorities and publicly funded bodies) involved in
promoting recreational sport and providing recreational facilities,
(Irish Sports Council Act, 1999, Part 1, Sect. 6(1))
By measuring levels of participation over time in different kinds of grassroots sport, the ISM is designed to be
part of the policy architecture, contributing to the evaluation of sports policy as defined.
Limitations of the ISM
As with any survey instrument, there are limitations associated with the methodology and subsequent analysis
that should be borne in mind. Two issues are of particular relevance.
First, the survey reaches only people with a fixed line telephone, at home, who agree to take part. Hence, it is
possible that these factors bias the sample. To counter this, the ISM employs a selection rule regarding which
household member is asked to respond, based on gender, age and economic status. The data are reweighted by
six socio-demographic and socio-economic variables to match a 2007 population profile supplied by the Central
Statistics Office. Nevertheless, sample bias remains possible and is even likely with respect to certain hard-toreach groups, such as non-Irish nationals (see Chapter 4).
Second, survey data rely on accurate responses from individuals regarding their own behaviour. There may
be an incentive to misreport, especially if the behaviour in question could be seen in a judgemental light.
One tactic for avoiding misreporting is to demand detail on activities, which the ISM questionnaire does.
Nevertheless, potential misreporting is unavoidable.
A further research strategy employed to counter these limitations is to compare the findings here with those
of other published surveys that used different methodologies. In that regard, many findings in this report are
compared to the 2003 SSPE and the 2006 QNHS, each of which was a face-to-face survey. In general, there is
close accordance in the results.
Part Two:
Physical Participation
10
2. How Active Are We?
Highlights
• In 2007, 24% of the adult population could be classified as “Highly Active”, 28% “Fairly Active”, 30% “Just
Active” and 18% “Sedentary”
• 33% played sport for at least 20 minutes during the previous 7 days
• 58% went for a recreational walk of at least 20 minutes during the previous 7 days
Introduction
The aim of this chapter is to combine the information obtained on participation in sport and walking to provide
headline figures for recreational physical activity among the Irish population. The concentration here is on
recreational activities, although the ISM does include questions on whether people walk or cycle regularly for
transport. There are, of course, other forms of physical activity (e.g. manual labour, gardening, housework etc.)
which are not factored into the analysis.
Key Results
We classify the population into a hierarchy of four groups defined by levels of recreational physical activity
during the previous week. Table 2.1 lists and defines these groups. The most active (“Highly Active”)
corresponds to those people who through a combination of recreational walking and playing sport meet current
WHO guidelines for physical activity, which recommend at least 30 minutes of moderate exercise five times a
week (World Health Organisation, 2003). In the present context, “moderate” physical activity is defined as sport
or exercise activity that “raises the breathing rate” or recreational walking at a “steady” pace or faster.
Table 2.1: A hierarchy of levels of physical activity based on the ISM questionnaire
Category
Definition
Highly Active
Participated in 30 minutes moderate physical activity at least five times during
the previous 7 days (i.e. met WHO guidelines)
Fairly Active
Participated in 30 minutes moderate physical activity at least twice during the
previous 7 days
Just Active
Participated in a sporting activity or recreational walking for 20 minutes at least
once during the previous 7 days, or regularly cycles or walks for transport (at
least once-a-week)
Sedentary
Did not participate (20 minutes) in recreational activity during the previous 7
days and does not cycle or walk regularly for transport
The figures throughout the report are given as percentages. For the adult population aged 16 plus in 2007, 1% is
approximately 34,000 people.
11
A breakdown of the population into this hierarchical
classification of physical activity levels is presented in
Figure 2.1. Just under 24% of adults are classified as
Highly Active, but over half of the adult population is
either Highly Active or Fairly Active. Some 18% of the
population is effectively Sedentary. Of note, however, is
the large proportion of adults, very nearly 30%, who do
a small amount of physical activity, walking or playing
sport just once a week, or engaging in physical activity
only for transport.
Figure 2.1: Population classified by levels
of recreational physical activity
Highly Active 23.9%
Sedemtary 18.2%
Just Active 29.8%
Fairly Active 28.2%
For the purposes of future comparison of levels of playing sport and walking, i.e. to define figures against
which to judge future performance, we require thresholds for being counted as a participant in each of these
activities. The ISM questionnaire asked respondents about the length of recreational walks and the duration of
sessions of playing sport undertaken in the previous 7 days. Analysis of this data reveals a sharp step-jump in
the distribution of both variables, which occurs between 15 and 20 minutes duration. Based on this analysis,
we determined that a person is counted as a “player” or a “walker” respectively if they played sport (excluding
walking) or walked for at least 20 minutes at least once during the previous 7 days.
In 2007, the proportion of Irish adults who participated
in sport (excluding walking) for at least 20 minutes
during the 7 days prior to the survey was as follows.
In 2007, the proportion of Irish adults who participated
in recreational walking for at least 20 minutes during
the 7 days prior to the survey was as follows.
Players: 32.9%
Walkers: 58.1%
Discussion
Since the questionnaire and methodology of the ISM is being used for the first time, it is not possible to
compare the figures above with results from previous surveys, such that we can assess with any degree of
precision whether active physical participation is rising or falling. Rather, we anticipate that these headline
figures will provide a solid basis for comparison in future years.
Nevertheless, it is comforting to note that the numbers presented in this chapter are broadly in line with
expectations based on previous surveys, more specifically the Survey of Sport and Physical Exercise (SSPE) of
2003 and the Quarterly National Household Survey (QNHS) of 2006.
Based on the SSPE, Fahey et al. (2004) estimated that some 33% of the population were active participants in
sport more than once a month, while 22% were effectively sedentary. A precise comparison with the figures
presented in this chapter is, however, not reliable, since the definitions of participation employed are not exactly
the same and the minimum age of respondents is also different (it was 18 years in the SSPE). Still, despite the
different methodology (telephone versus face-to-face) and reference period (7 days versus 12 months), the
headline figures above are in close accordance with those recorded by the SSPE.
The QNHS data are more difficult to compare. In the QNHS survey, walking was included in a long list
of possible sporting activities, rather than being examined via separate questionnaire items that presented
respondents with a clear definition of recreational walking, as for the SSPE and ISM. Hence, the published
headline figures for participation arising from the survey combine walking and playing other forms of sport
(CSO, 2007). Furthermore, the proportion of the population estimated to have taken a recreational walk during
the previous 12 months was just 25%. This figure is unrealistically low, both intuitively and in comparison to
other estimates. Given the questionnaire design, it cannot be regarded as reliable. Still, it is possible to make a
rough comparison between the ISM and QNHS data by removing the walkers from the QNHS participation
rates. Unfortunately, the comparison can only be made by making some assumptions about the relative
frequency, intensity and duration of walking sessions versus sessions of playing sport. Nevertheless, using this
method we can determine that the proportion of the population participating in sport (excluding walking) at
least once a week in the QNHS sample is approximately 30% and certainly unlikely to be greater than 33%.
Although this comparison is approximate, the ISM figures again compare reasonably.
12
This chapter thus offers baseline figures for the levels of recreational physical activity and, more specifically, for
playing sport and walking in 2007. Given the relationship with previous estimates of participation, we can have
a degree of confidence in the reliability of the figures, which should serve as a benchmark against which future
estimates can be compared.
A final point to note here surrounds the role of walking and cycling for transport, which previous surveys have
not recorded. Although we have no information as to the frequency, duration and intensity of these activities,
the ISM records that 41.1% and 10.4% respectively walk and cycle for transport, for at least 20 minutes every
week. These figures contribute to the physical activity classification above, but they are arguably surprisingly
high in their own right. While there can be little doubt that car usage in Ireland has greatly increased, walking
and cycling to get from A to B appears still to make a substantial contribution to physical activity.
13
3. FITT Analysis
Highlights
• There was variation by season: fewer people played sport towards the end of the year
• 68% of participants played more than once a week, 69% with high effort
• 62% played their sport in a non-organised setting, with family, friends or alone
Introduction
This chapter analyses the responses of players to the FITT questions (‘Frequency, Intensity, Time and Type’). A
separate analysis for walking is given in Chapter 7. FITT is a standard method for recording physical activity
which takes account of the frequency of participation, the level of physical effort, the duration of activity and
the type of activity undertaken. The ISM questionnaire records this information for up to three sports played
in the previous 7 days. In addition, because the ISM collected data throughout the year, it begins by examining
seasonal variation in participation – an issue that has not previously been possible to address.
Key Results
As detailed in Chapter 2, 32.9% of Irish adults played
some form of sport for a period of at least 20 minutes
during the previous 7 days. There was, however,
significant variation across seasons, as Figure 3.1
shows. The slight drop in the proportion who played
sport during the second quarter of the year is not
statistically significant, but the more marked fall-off in
the final quarter is.
Figure 3.2 reveals that the seasonal variation was
not consistent across different kinds of sports. Over
the year, more than two and a half times as many
people played individual sports (26.2%) as played
team sports (9.7%). But the end of year fall-off
was due to a drop in individual sports, which was
consistent across many activities. It is not clear what
caused it or, indeed, whether the effect is merely
seasonal or more enduring. Data from 2008 will
help to assess this.
14
Figure 3.1: Proportion playing sport
by season
40
35
34.9
32.5
34.7
29.5
% 30
25
20
Q1
Q2
Q3
Q4
Figure 3.2: Proportion playing individual
and team sport by season
30
26.6
27.6
27.6
25
23.2
20
% 15
11.6
10
7.7
10.6
8.7
Q3
Q4
5
0
Q1
Q2
Individual
Team
As shown in Figure 3.3, over 7% of adults had played
more than one sport in the previous 7 days, with 1.7%
playing three or more sports. The proportion playing
more than one sport equates to one quarter of players.
This contrasts with Fahey et al. (2004), who found just
over half of players participated in more then one sport.
But the reference period for that study was 12 months,
whereas here it is 7 days. It is likely that some players
switch between sports by season. Another possibility is
that a substantial number of players participate in one
sport regularly and another occasionally.
Figure 3.3: Proportions playing none, one,
two or three sports
As Figure 3.4 shows, more than two-thirds of players
took part in sport more than once during the previous
week, with almost one quarter playing four times or
more. Most people who engaged in multiple sessions
of sport performed the same activity on each occasion.
This indicates that there is a substantial degree of
polarisation in participation in sport. The large
majority of sporting activity is not that of “occasional
players”, and some 8% of the adult population plays
sport on more days than they do not.
Figure 3.4: Number of sessions of players
during previous week
The majority of sessions of playing sport lasted
between 30 minutes and one hour (Figure 3.5). This
distribution is partly explained by the popularity of
individual sports, for which almost two-thirds of
sessions take up to an hour (golf being the exception).
In contrast, 60% of team sport takes longer than
an hour to play. This is in keeping with evidence
suggesting that the growing popularity of individual
activities reflects the ease of fitting them around other
time commitments, such as work and family (Lunn
and Layte, 2008).
Figure 3.5: Length of sessions of playing
sport
As shown in Figure 3.6, almost 86% of players said
their exertions in a typical session were sufficient to
raise their breathing rate noticeably, with 69% saying
a session usually left them out of breath or sweating.
Playing a team sport is more likely to involve high
levels of effort, but players of team sports also tend to
be younger. For individual sport, which is more likely
to be played by older adults, 83% of sessions still
involve sufficient effort to raise people’s breathing
rate noticeably.
Figure 3.6: Degrees of effort
Two 5.7%
Three 1.7%
One 25.5%
No Sport 67.1%
Six+ 9.4%
Five 5.4%
One 32.2%
Four 8.9%
Three 16.8%
Two 27.3%
60
50
40
% 30
20
10
0
Up to 30
31 - 60
61 - 90
91 - 120
120+
Minutes
Little Effort 14.2%
Out of Breath /
Sweating 69.3%
Raised Breathing 16.5%
15
Figure 3.7 shows that less than 40% of sport was
played in organised sessions, the majority of that
being in organised training or classes rather than a
competitive setting. More than a third of sporting
activity took place with family or friends, which was
the most common context for sporting activity. Lastly,
more than a quarter of sporting activity was solitary,
almost all of which was accounted for by personal
exercise activities, swimming, cycling and running. Of
course, much of the “non-organised” sport may have
involved facilities provided by a club or sports centre,
or a suitable public space.
Figure 3.7: Context in which sport is played
Organised
Session 22.6%
On Own 27.1%
Organised
Competition 15.1%
Family or
Friends 35.3%
The analysis thus far has looked at each component of FITT (fitness, intensity, time and type) in isolation, rather
than the relationship between them. Given the many different types of activities, one might not expect to find
strong general relationships between different components of FITT, yet there are regularities regarding what
types of participation are likely to be most intensive.
Figure 3.8: Intensity of playing by number
of sessions
% Out of Breath / Sweating
Figure 3.8 reveals that those who take part in more
sessions per week are also more likely to do so
intensively. Just over half of those who played just one
session in the previous 7 days put in enough effort to
be out of breath or sweat. For those participating more
than every other day, the figure is more like 80%. This
finding suggests further polarisation in the degree of
physical activity associated with participation in sport.
100
80
60
40
20
0
One
Two
Three
Four
Five
Sport Sessions
Figure 3.9: Intensity of playing by context
% Out of Breath / Sweating
There is also a relationship between the intensity of
playing and the context in which the activity takes
place, as Figure 3.9 makes clear. Activities undertaken
with family and friends tend to be less intensive,
perhaps because children are also involved. Activity
undertaken by people on their own tends to be
as demanding as that undertaken in competition,
primarily because the solitary activities undertaken
tend to be geared towards personal fitness.
100
80
60
40
20
0
Organised Organised
Session
Comp.
Family or
Friends
On Own
Discussion
The seasonal variation in sporting activity identified in this chapter is sizeable. Further analysis (not shown)
reveals no distinct pattern in the end of year fall-off by gender, age or socio-economic group. Rather, it seems
to have a broad impact across those who play individual sports. This effect does not, therefore, have an obvious
explanation. It is possible that a number of seasonal influences are involved, such as the weather, the approach
of Christmas, upheaval associated with the new academic term, and so on. An intriguing alternative is that the
effect is not seasonal but is associated with the rapidly deteriorating economic climate during late 2007. If so,
we might anticipate a continuing impact on participation in sport in 2008. From the 2007 data alone, it is not
possible to test this.
16
Previous research has shown that the biggest disparity in health status occurs between people who participate
in no sporting activity and people who play at least some sport, rather than between those who play sport
to differing degrees (Fahey et al., 2004; Lunn and Layte, 2008). In keeping with this, it is a primary focus of
policy to concentrate on getting people who do not participate actively in sport and exercise to take up some
form of activity. The analysis presented in this chapter supports this as an appropriate goal for policy. Once an
individual is engaged in a sport or exercise activity, there is a good chance they will participate more than once a
week, for longer than half-an-hour and that they will do so sufficiently to get out of breath or sweat. Thus, most
participants would be likely to get some degree of health benefit from their participation. The key issue remains
whether they are an active participant in the first place.
Nevertheless, the findings with respect to the context in which people play sport are also noteworthy as regards policy
that aims to increase participation. The majority of sporting activity is occurring beyond or on the fringes of official
sporting organisations. This strongly implies that policy mechanisms that rely on the pre-existing sporting bodies have
limited scope unless those bodies can reach out beyond the sporting and social networks they currently engage with.
As regards the social benefits of sport, the fact that 27% of activity is undertaken by people on their own is
striking. The individual sporting activities involved (going to the gym or other similar exercises, swimming,
running, cycling) are forms of participation previously identified as the fastest growing sporting and exercise
activities over recent decades (Lunn and Layte, 2008).
Previous research has also identified that the primary reason cited by non-participants for not playing sport is
lack of time (Fahey et al., 2004; CSO, 2007). The solo activities identified are highly efficient forms of exercise,
which take up little time and do not require much in the way of coordination between people. There may
therefore be a trade-off between the health benefits that such solo exercise activities bring and the social benefits
that accompany other types of participation.
17
4. Comparison of Social Groups
Highlights
• People with high educational attainment, men, younger people and those on high incomes were much more
likely to play sport and much less likely to be sedentary
• The estimated impact of income on the likelihood of playing sport was even higher than previously reported
• Non-Irish nationals, from outside the EU and the English-speaking countries, were approximately half as
likely to play sport as Irish nationals
Introduction
Research has shown substantial differences in rates of participation in sport and recreational walking by social
group (Fahey et al., 2004; Lunn, 2007a; CSO, 2007). In this chapter, we concentrate on how two of the headline
statistics defined in Chapter 2 vary by social group: active participation in sport (excluding walking) and being
sedentary. These are selected because the greatest differences in health benefit are found between those who
do no sport or physical activity and those who do at least some (Fahey et al., 2004; Lunn and Layte, 2008).
However, the social gradients reported below do not vary greatly whichever measure of activity is employed. All
the findings reported derive from multivariate models, an example of which is given in Appendix C.
Key Results
Figure 4.1: Playing sport and being
sedentary by educational attainment
% Out of Breath / Sweating
Data from the ISM confirm the findings of Lunn
(2007a) that the four most significant factors
associated with playing sport are educational
attainment, gender, age and income. Figure 4.1 shows
that people with higher educational attainment were
much more likely to have played sport for at least
20 minutes during the previous 7 days, and were
significantly less likely to have been sedentary (not
played sport, nor taken a walk, nor walked or cycled
for transport). The role of educational establishments
in promoting and aiding sporting activity is
particularly highlighted by the results for current
students (final column).
50
40
30
20
10
0
Primary
Played
Junior
Leaving
Cert
Cert
Sedentary
*Other
2nd Level
Third
Level
Current
Student
* Other 2nd Level” refers to post-school qualifications below degree or diploma level.
Previous research has also shown interesting interactions between age and gender – the likelihood of playing
sport or being sedentary follows a different pattern across the life courses of men and women. The large sample
of the ISM allows a more fine-grained analysis of these effects.
Participation rates for playing sport are higher among
men and decline with age. But the gender difference
is not constant, as Figure 4.2 reveals. The gender gap
narrows during early adulthood and is narrowest for
the 46 – 55 age group. However, participation is again
lower for older women.
Figure 4.2: Playing sport by gender and age
70
60
50
%
40
30
20
10
0
16-25
Male
18
26-35
Female
36-45
46-55
56-65
66+
Figure 4.3 reveals an even more complex pattern
by gender and age with respect to being sedentary.
Although less likely to play sport, young women are
significantly less likely to be sedentary than young
men. For both genders, the likelihood of being
sedentary rises, falls and rises again across the age
categories, albeit at slightly different stages. Women
are generally less likely to be sedentary than men until
old age, when the effect reverses.
Figure 4.3: Being sedentary by gender
and age
35
30
25
%
20
15
10
5
0
16-25
Male
26-35
36-45
46-55
56-65
66+
Female
These interactions between gender and age are easier to explain for playing sport than for being sedentary.
Following the sporting life-course analysis of Lunn and Layte (2008), the pattern of Figure 4.2 probably
results from the combination of two separate effects. First, men are far more likely to play team sports
during earlier adulthood, while women are more likely to play individual sports, for which the drop-out
rate is considerably lower. Hence, men drop out more quickly, causing the gender gap to narrow towards
middle-age. Second, the lower level of participation among older women is probably a cohort effect, rather
than an age effect. Many of the current generation of older women left school prior to the expansion of
Irish education in the late 1960s, which increased greatly the opportunities for females to play sport. The
participation rate of this group has been low throughout their lifetimes and many have never played any sport
at all. Once both these factors – the high drop out of young men from team sports and the cohort of older
women who have never played sport – are taken into account, the pattern in Figure 4.2 makes sense: the
gender gap first narrows with age and then widens again. Note that it is therefore unlikely that the gender gap
evident among these older age-groups will continue, as current middle-aged women play much more sport
than their mothers’ generation did.
The patterns for being sedentary (Figure 4.3) are more complex. The same kind of cohort effect may well be at
work for older women – a generation for whom regular physical exercise was simply not the norm. For other
age groups, women are less sedentary on account of the fact that they do much more walking, even in the
youngest age group (see Chapter 7). But the pattern whereby the likelihood of being sedentary first rises then
falls, before rising again in old age, is harder to fathom. It seems to result from a combination of effects that
impact upon walking, which is related to a broader range of background characteristics than playing sport,
including partnership and labour market status, (see Chapter 7).
Figure 4.4 presents a striking picture of the socioeconomic gap in sport and physical activity. People
on low incomes were two to three times more likely
to have been sedentary in the previous 7 days than
to play sport, while those in the richest group were
four to five times more likely to play sport than be
sedentary.
Figure 4.4: Playing sport and being
sedentary by weekly net household income
60
50
40
30
20
10
The pattern revealed by Figure 4.4 is even more
0
arresting than the impact of income reported in
<�300
300-399
400-499 500-749 750-899 900-1249 �1250+
previous research (Lunn, 2007a). That is, the gradient
Played
Sedentary
of activity with income is stronger than had been
found in the SSPE data. It is very unlikely that this
results from a change in the behaviour of different
income categories since 2003, when the SSPE was conducted. Rather, it probably stems from the fact that the
income question in the present survey was answered by a higher proportion of people and therefore probably
measured household income more accurately. Lunn (2007a) commented that the measurement error associated
with income would be likely to result in an underestimate of its true impact. The current findings appear to
confirm that hypothesis.
19
Lunn (2007a) found no impact on playing sport of
occupational class, for a given level of educational
attainment and income. With the larger sample of the
ISM, however, it is possible to find an effect. As Figure
4.5 charts, those in manual occupations play less sport.
Multivariate analysis shows this to be true even once
the impacts of educational attainment and income are
controlled for, though the effect is not as large as for
those two factors. This finding could be due to people
in manual jobs being disinclined to further physical
activity. The similarity in behaviour to those who have no
occupation suggests, however, that membership of a lower
social class may be behind the result (see Discussion).
Figure 4.5: Playing sport and being
sedentary by type of occupation
40
30
% 20
10
0
Non-manual
Played
Manual
No occ
Sedentary
The large sample-size allows us to estimate participation among non-Irish nationals. The results must be treated with
caution, however. In the sample, 7.7% of respondents were non-Irish, which compares to 11.3% in Census 2006.
Predictably, with a telephone-based survey, nationalities whose citizens are likely to be non-English-speaking are
those most underrepresented. For these nationalities, the people sampled are probably those with better English. It is
a reasonable (though arguable) hypothesis that they would find it easier to be socially active and hence to play sport.
Thus, the figures below probably underestimate the impact of nationality.
Figure 4.6 details variation in levels of playing by
nationality. The results need further qualification,
however, as the demographic profiles of the groups
are different. In particular, British nationals have an
older profile, while other nationalities have a younger
profile. Once these factors are accounted for in
multivariate analysis, the only significant difference is
that those in the category ‘Rest of World’ (RoW) are
less than half as likely to play sport.
Figure 4.6: Playing by nationality
50
40
%
30
20
10
0
Irish
British
Other EU
Other
Anglo
RoW
(Although the survey sampled a reasonable number of non-Irish nationals, the sample-size is still too small to
examine sedentary behaviour, which has a lower incidence than playing sport and results in unreliably small
cell-sizes.)
In addition to the social groups considered above, there are a number of other significant findings with respect to
social groups and the likelihood of playing sport. People who are disabled, people who do not own a car (especially
older people) and people who are unemployed were less likely to have played sport in the previous 7 days. Retired
people were more likely to have played than people of the same age still working, as were people in home duties.
20
Discussion
The analysis presented in this chapter is in keeping with previous analyses of playing sport and physical activity
by social groups, yet the larger sample size of the ISM permits additional insights.
Educational attainment, gender, age and income are the most powerful factors associated with having played sport
in the previous 7 days. The gradient of participation with educational attainment is very striking and the particularly
high levels of activity among the workable sample of almost 400 students in the data-set confirms the hypothesis that
continuing education plays an especially important role in adult sporting participation (Lunn, 2007a).
The pattern by age and gender is in keeping with previous findings, although with the larger sample size of the ISM it
is possible to discern greater variability in physical activity across the life-course of women than is the case for men.
Compared with previous research, the importance of household income emerges more strongly from the ISM,
probably because it was measured with more accuracy. This does not necessarily mean that expense is a reason
why people do not participate, although it may imply that. High income is associated with many factors that
could influence whether an individual plays sport or is sedentary, including living in better local environments,
with better transport connections and access to local organisations and facilities.
Two new findings reported in this chapter concern the association between participation and occupational
group, and between playing sport and nationality. Dealing first with the former, although previous crosssectional analysis failed to find a significant impact of occupational class, survival analysis conducted by Lunn
and Layte (2008) found that those in professional occupations were more likely to take up sports as adults.
Given this and the similarity between rates of participation for those in less skilled occupational groups and
those with no occupation, it is perhaps more likely that the association between occupational group and playing
sport is primarily due to the advantageous social networks and associated opportunities enjoyed by those in
higher occupational groups, rather than to the demands of manual jobs.
Turning to the issue of nationality, despite the fact that the participation rate recorded for non-EU and nonEnglish-speaking nationalities is probably an overestimate, adults in this category, mainly Asian and African
immigrants, are considerably less likely to play sport. It is interesting to note, however, that there is no evidence
here that non-British immigrants from the EU play less sport.
Overall, the patterns of playing sport and physical activity by social group remain dramatic and suggestive of
powerful social forces that determine people’s opportunities. These disparities therefore remain one of the major
challenges for sports policy.
21
Figure 5.1: Proportion playing sport by county/council
50
42.4
40
%
40.1
37.0
36.4
36.3
35.5
35.4
35.4
35.1
34.7
34.4
34.2
34.0
33.6
32.7
G
MO
MN
MH
WW
CN
LD
24.6
24.3
23.7
30
20
10
0
D(F)
D(DLR)
WD
D(S)
CE
WX
C
LK
31.0
30.6
30.4
30.1
29.2
29.1
29.1
28.6
50
40
%
30
21.9
20
20.7
18.0
16.5
10
0
KK
CW
LH
LS
DL
D(CC)
TS
LM
SO
OY
RN
KE
KY
TN
WM
Figure 5.2: Likelihood of playing sport by county/council, controlling for social background
2
Odds Ratio
1.61
1.5
1.30
1.26
1.23
1.20
1.19
1.17
1.11
1.11
1.10
1.08
1.07
1.03
1.02
G
WX
1
1.00
0.5
0
D(DLR)
MO
MN
KK
D(S)
WW
LH
DL
MH
D(F)
CE
C
0.99
0.99
0.98
0.96
0.91
0.89
0.87
0.84
0.76
0.75
0.68
0.66
SO
Odds Ratio
2
1.5
1
0.64
0.50
0.5
0.33
0
TN
22
CW
WD
KY
RN
TS
CN
D(CC)
LS
LK
LD
KE
OY
LM
WM
5. Comparison by County/Council
Highlights
• Comparing the highest performing areas with the lowest performing areas, more than two-and-a-half times
as many people played sport in the previous 7 days
• Controlling for population profile, Dún Laoghaire-Rathdown and Mayo recorded high participation
• Controlling for population profile, Dublin City, Limerick, Kildare, Offaly, Leitrim and Westmeath recorded
low participation
Introduction
There is considerable variation in the level of playing sport across Ireland by county. Raw participation rates
are provided in this chapter, but this is not the best way to compare, because counties have very different
socio-demographic and socio-economic profiles. One cannot expect a poor county with an older population
to have the same number of people playing sport as a rich county with a young population. Hence, the better
comparison is one that takes account of these differences. From a policy perspective, a comparison that controls
for such factors indicates each county’s sporting performance relative to what can reasonably be expected.
Key Results
The survey collected information about which county respondents lived in. Those in Dublin were further asked
which of the four Dublin local authorities they lived in (Dublin City Council, Dún Laoghaire-Rathdown, Fingal,
and South Dublin). Those in Tipperary were also asked whether they lived in North or South Tipperary. Hence,
the results compare across 30 areas. Ideally, the survey would also have distinguished between certain cities and
counties (e.g. Cork, Galway, Limerick, Waterford), but limitations of survey space prevented further refinement
by geographic area. Participation rates by county are provided in Figure 5.1, which employs the county
abbreviations from vehicle registration plates.
Fingal and Dún Laoghaire-Rathdown have participation rates of over 40%, well above the national average of
33% and ahead of a clump of areas with participation rates in the high thirties. At the other end of the spectrum,
Tipperary North and Westmeath are the only counties in which less than 20% of respondents had played during
the week prior to the survey. Furthermore, there is an asymmetry in the raw data. The areas with the lowest
participation rates are further below the average participation level than those with the highest participation
rates are above it.
It is important to note, however, that there is a relatively high margin for error on these raw estimates. The
average sample-size for each area is 325, but for those outside Dublin, Cork, Limerick and Galway it is only 224.
Nevertheless, in some areas more than two-and-a-half times as many people were recorded playing sport as in
others. Even with the low sample sizes, it is possible to test for the statistical significance of such large differences.
23
As stated above, however, it is important to note that these raw figures do not take account of the population
profile differences between areas. The analysis presented in Figure 5.2 does, but requires some explanation.
The figures given are odds ratios. They express the relative odds that an individual in each area plays sport,
controlling for population profile. The numbers are expressed relative to County Sligo, which is the median area
(i.e. the middle-ranked one) and takes the value 1.0. Hence, we estimate that a person of a given gender, age and
socio-economic status living in Sligo is three times as likely to have played sport in the past 7 days as someone
with the same characteristics living in Westmeath. Similarly, a person with those characteristics living in Dún
Laoghaire-Rathdown is more than half as likely again to have played sport in the previous 7 days as the person
in Sligo, and almost five times as likely as the person in Westmeath.
These odds ratios are estimated using the multivariate statistical model presented in Appendix C, which
estimates the relationship between playing sport and a large range of socio-demographic and socio-economic
variables: educational attainment, age, income, employment status, occupational group, disability, whether the
family has children, car ownership, urban-rural location and nationality. Thus, the figures compare areas while
controlling for all of these factors.
How significant are the differences? Not all of the differences between counties are statistically significant, in
part because some of the differences are small, but also because the sample size for each county varies and so the
estimate is less accurate for the areas with lower populations. The different colours of the columns identify those
areas where the difference in levels of participation is statistically significant (at the 10% level) compared with
the median ten areas – that is, the ten areas in the middle of the range when all 30 areas are arranged in order
of likelihood of participation. The two orange columns, for Mayo and Dún Laoghaire-Rathdown, indicate that
both areas had significantly higher participation in sport in 2007. The green columns for Dublin City, Limerick,
Kildare, Offaly, Leitrim and Westmeath, indicate that these areas had significantly lower participation. The
greater number of areas significantly below median performance confirms the asymmetry suggested by the raw
data in Figure 5.1.
Discussion
It is important to note that the ranking of counties given here does not necessarily imply anything about the
success or otherwise of local sports policy, or the performance of Local Sports Partnerships and local authorities
more generally. Clearly, a successful local sports policy is one important factor in determining the level of
participation in a given area, but it is only one among many other potential influences on the numbers playing
sport. Other important factors may include transport infrastructure, long-standing tradition, the prevalence of
recent arrivals in the area, the number of new developments, the likelihood of people staying in the area after
leaving school, the presence of third-level institutions and so on. These factors are planning and demographic
issues that are largely or entirely outside the scope of sports policy.
The comparison between counties and councils is nevertheless very useful from the point of view that it allows
policy makers to identify areas where there is likely to be considerable opportunity to raise participation rates.
Areas with low likelihoods of individuals playing sport are more likely to be home to people who are interested
in sport but currently do not play. Thus, those areas with the lowest likelihoods of playing should be considered
areas likely to have high levels of untapped interest and hence where the most rapid rises in participation might
potentially be achieved.
24
6. Relative Popularity of Sports
Highlights
• Personal exercise activities (going to the gym, fitness classes, exercise machines etc.) are now the most
popular sport and exercise activity in Ireland, followed by swimming
• Soccer is by far the most popular team sport, but ranks poorly among women relative to other sports
• Combining volunteering, membership and attendance, Gaelic games remain the leading sports for social
participation, but there are now more gym members than GAA members
Introduction
The size of the sample, at nearly 10,000, allows a fairly precise ranking of individual sports by participation rate
for the four primary forms of participation: playing, volunteering, club membership and attendance. (See Part
Three for details on these later forms of participation). This analysis differs from previous analyses (Fahey et al.,
2004; CSO, 2007), however, in that the reference period is one week instead of one year. Thus, seasonal sports
are likely to register at a lower participation rate than activities that are played consistently all year round.
Key Results
Table 6.1 lists the most popular sports (excluding walking) according to the percentage of the population that
played the sport in the previous 7 days. Those who played more than one sport are counted under each sport
they played. The ‘Personal Exercise’ category is mostly made up of people “going to the gym” or “working out”,
but it includes aerobics and fitness classes. ‘Swimming’ includes aquarobics; ‘Soccer’ includes five-a-side; ‘Golf ’
includes pitch and putt; ‘Cycling’ includes cycling for leisure (but not for transport); ‘Rugby’ includes tag rugby.
In fact, these broad definitions make little difference to the results and no difference to the ordering of sports,
although if cycling for transport were included, cycling would top the table at 11.7%.
Table 6.1: Most popular ten sports for active participation
Sport
%
Personal Exercise
7.3
Swimming
6.7
Soccer
5.9
Golf
5.2
Jogging
3.1
Cycling
2.5
Gaelic football
2.3
Dancing
1.9
Hurling/Camogie
1.3
Rugby
0.9
25
As Table 6.2 reveals, there are considerable differences in the ranking of sports for each gender. Of particular
note is the importance of soccer in men’s sport and the dominance of women’s sporting activity by individual
sports – only one team sport, Gaelic football, makes it on to the list and at a very low level.
Table 6.2: Most popular ten sports for playing by gender
Male
%
Female
%
Soccer
11.4
Personal Exercise
8.5
Golf
8.7
Swimming
7.9
Personal Exercise
6.2
Dancing
3.0
Swimming
5.5
Jogging
2.0
Jogging
4.2
Golf
1.9
Gaelic football
3.9
Yoga
1.3
Cycling
3.8
Tennis
1.2
Hurling
2.3
Cycling
1.2
Rugby
1.9
Gaelic football
0.8
Dancing
0.8
Horse riding
0.5
There are some notable differences between the results reported here and those reported previously. The
analysis confirms the finding of the CSO (2007), based on the 2006 QNHS, that personal exercise activity is now
the most popular form of sport and exercise in Ireland. Fahey et al. (2004) had found swimming to be the most
popular, based on the 2003 SSPE. But historical trends constructed from recall data by Lunn and Layte (2008),
show a dramatic rise in personal exercise activity, beginning in the mid-1980s. A continuation of these trends
predicted that it would surpass soccer and swimming within a few years of the 2003 survey on which the trends
were based. This prediction has come to pass. These trends also explain the higher ranking of jogging and yoga
seen here, which are also fast growing individual activities.
Two other specific sports are worthy of mention in the context of previous work. First, although the margins of
error involved make it difficult to be sure, the presence of rugby in the list of most popular sports may indicate
that the common perception of its rising popularity is accurate. Rugby did not even feature in the top 15 male
sports in Fahey et al. (2004), although the presence of 16 and 17 year-olds in the present survey could also be
an important factor. Second, it is worth noting the popularity of dancing, among both genders, which was not
included under the definition of sport and exercise in the previous studies.
Overall, however, the results confirm the observations of Lunn and Layte (2008) that individual sports are
outpacing team sports in popularity, with soccer being the traditional team sport that comes closest to keeping up.
Turning to social participation, given the reference period of just 7 days, it is not possible to produce a full ranking
of sports for volunteering, as the samples for each individual sport are too small. It is nevertheless clear from
the data that the GAA remains the outstanding example regarding sports-related volunteering, with 3.6% of the
population having volunteered in some way during the previous 7 days. It is interesting to note that as many adults
volunteer for the GAA each week as actually play Gaelic games. The only other sport to register a significant
number of volunteers in the survey was soccer, at 2.2%. These figures are clearly related to the dominance of Gaelic
games and soccer in children’s sport, which accounts for a substantial amount of volunteering activity.
Table 6.3 ranks sports according to the prevalence of club membership. Almost 10% of adults are now members
of a gym, fitness centre or health club. Unsurprisingly, there is a strong correlation between club members and
active participants. Yet it is interesting to compare Tables 6.1 and 6.3. A sizeable proportion, though not all, gym
members had used the facility during the previous week. Meanwhile, the GAA has many more club members
than players – doubtless linked to its high rates of volunteering and attendance (see below).
26
Table 6.3: Ranking according to club membership
Sport
%
Personal Exercise
9.8
GAA (Football/hurling)
8.4
Golf
5.8
Soccer
4.1
Swimming
1.9
Rugby
1.5
Tennis
1.2
Mixed sports
0.7
One point to note is that two of the more popular sports stand out, in that they mostly require facilities or
appropriate public space, yet have considerably lower membership rates than active participation rates. For
swimming this probably reflecting the prevalence of pay-per-use pools, but perhaps also the number of gyms/
health clubs that have pools. But it is also true of soccer, especially in comparison to Gaelic games and rugby.
The social structure surrounding soccer is clearly much more informal. Although other interpretations are
possible, it seems reasonable to suggest that there is scope in both these sports, especially soccer, for improved
social organisation.
Table 6.3 is in close accordance with the SSPE findings for membership rates (Delaney and Fahey, 2005)
although, again, the growth in personal exercise activities is reflected. In 2003, GAA clubs had the highest rates
of membership of all sports clubs. Now, they have been surpassed by gyms and fitness centres. There is little
overlap here: less than 5% of gym members are GAA members.
Table 6.4 confirms the important role of Gaelic games in communities, showing that Gaelic football and
hurling/camogie account for a large proportion of attendance at fixtures and sporting events. Indeed, it is the
traditional team sports that dominate for spectators. This is doubtless due to the fact that many individual
sporting activities are less of a spectacle, but it is also because parents like to watch their children play sport
and the traditional team sports continue to be among the most popular children’s sports, albeit primarily with
respect to boys. Again, these patterns are in accordance with previous findings (Delaney and Fahey, 2005).
Table 6.4: Ranking according to attendance
Sport
%
Gaelic football
6.3
Soccer
4.5
Hurling/camogie
3.8
Rugby
1.1
Golf
0.3
Swimming
0.3
27
Discussion
Apart from providing further evidence of the dramatic increase in personal exercise activities, the figures
presented here for volunteering, club membership and attendance do not add much to our previous
understanding of how these forms of participation vary across the range of sports. The 7 day reference period
employed in the questionnaire is a superior data collection method for gauging the level of active participation
in sporting activities (i.e. playing), but perhaps not such a good one for examining other forms of participation,
which tend to be more infrequent and so register only at low levels for most sports.
On the other hand, for measuring the participation rate for playing each sport, the data generated here are
probably the best indication of the relative participation rates across sports that have been made available in
Ireland to date. Although the CSO (2007) figures are based on a larger sample, the published figures do not take
account of the significant number of people who play multiple sports. They are also based on a less accurate 12
month reference period.
Nevertheless, the results from the ISM are not out of line with previous work. With the exception of soccer, it
is individual sports, especially personal exercise, swimming, golf, jogging and cycling that dominate grassroots
participation in adult sport and exercise. Given the emphasis placed on traditional team sports in both the
media and policy, in part driven by the understandable popularity of these games as spectator sports, there
remains a real challenge for sports policy to promote activities that are more popular among adults and also
likely to be of greater health benefit to people as they get older.
Another important aspect of the results presented in this chapter is the comparison of active participation and
club membership. For swimming and soccer, but perhaps especially the latter, it suggests the possibility that the
social organisation could be strengthened.
28
7. Walking
Highlights
• 14% of the population went for a recreational walk every day the previous week, while 42% did not take a
walk at all
• Women walk more than men and seem to be a strong influence, since men in couples walk much more than
single men
• 40% walk regularly for transport, although the figure is much lower in rural locations
Introduction
The ISM records more detailed information about the walking habits of Irish adults than has been collected
previously. Respondents are asked whether they have taken any walks for exercise, recreation or leisure in the
previous 7 days. They are then requested to give the approximate number of minutes for each walk and to
describe their usual walking pace.
Key Results
In 2007, 58% of people had taken at least one walk
of over 20 minutes or more for recreation or leisure,
within the previous 7 days. There was, however,
considerable seasonal variation, as depicted in Figure
7.1. In the second quarter of the year, the figure
reached as high as 62%, while in the final quarter it
fell to 54%. Given that 2007 had a particularly poor
summer, it is possible that the seasonal variation in
the proportion of people walking will, in general,
prove to be greater still.
Figure 7.1: Proportion walking at least 20
minutes per week by season
The mean number of walks per person per week
was 2.3, but the distribution of the number of walks
across the population was polarised (Figure 7.2).
Some 14% of the population walked at least 20
minutes for recreation every day. Thus, a majority of
the population either walked every day or not at all.
The large majority of walks lasted between half an
hour and one hour and a quarter, with most people
describing their walking pace as “steady, average” or
“fairly brisk”.
Figure 7.2: Walks per week
65
60
%
55
50
50
40
%
Q1
Q2
Q3
Q4
42
30
20
10
0
6
0
1
12
2
14
13
3
6
6
4
5
2
6
7+
Walks per week
Analysis of walking by socio-demographic variables reveals that the influence of social background on whether
people walked is fairly weak – much weaker than in the case of playing sport (excluding walking). The
implication is that individual differences and other factors not addressed in the survey have a significant impact
on walking behaviour. Candidates for such influences might include dog-ownership and the attractiveness or
feasibility of local walks. Nevertheless, there are some statistically significant effects worth highlighting.
29
The likelihood that people had taken at least one
recreational walk in the previous 7 days displays a
strong pattern by gender and age. As Figure 7.3 shows,
middle-aged and, particularly, young women were
much more likely to have taken a walk than their male
counterparts, whose likelihood of having taken a walk
increased fairly steadily with age.
One interesting driver of male walking behaviour
appears to be whether the man is single or has
a partner. Even controlling for age and other
background characteristics, single men were far
less likely to take a walk than married or cohabiting
men, as Figure 7.4 indicates. Furthermore, habits
formed during partnerships appear to be lasting
– divorced and separated men continue to take walks.
Young single men, meanwhile, are the least likely
demographic group to take walks.
Figure 7.3: Walking by age and gender
%
80
70
60
50
40
30
20
10
0
16-25
26-35
Male
Female
36-45
46-55
56-65
65+
Figure 7.4: Walking by gender and
partnership status
80
70
60
50
% 40
30
20
10
0
Single
Males
Partnered
Females
Separated/
Divorced
A number of smaller but statistically significant factors also influenced walking for recreation. People of higher
educational attainment and higher income were somewhat more likely to have walked during the previous 7
days. Retired people were more likely to have taken a walk. People with small children were less likely to have
walked, as were non-Irish nationals. However, all of these differences are smaller than those reported above.
The complete picture, which is more difficult to convey presentationally, is that recreational walking is not as
strongly related to people’s background characteristics as other sport and exercise activities.
Respondents indicated separately whether they undertook regular walks for transport, as opposed to for
recreation, exercise or leisure. ‘Regular’ was defined as at least once a week. Of the total population, 40%
undertook regular walks for transport. Once again, the differences between individuals based on social
background were relatively small, but some were statistically significant.
The most significant differences in walking for
transport were associated with residential location.
People living in more densely populated areas are
much more likely to walk for transport, as shown in
Figure 7.5. There is clearly a greater degree of cardependency associated with living in rural Ireland,
which has an impact upon levels of physical activity.
A number of other characteristics increase the
likelihood that individuals walk to get from A to
B. Students, non-Irish people, single people (never
married), people living in social housing and those
who have no car are all more likely to walk regularly
for transport.
30
Figure 7.5: Regular walking for transport by
residential location
50
40
%
30
20
10
0
City
Town
Village
Isolated
Discussion
Because walking accounts for such a large amount of physical activity, the factors that influence whether people
walk for recreation or for transport are likely to have significant effects on people’s health.
However, it appears to be much less straightforward to identify strong factors that determine whether people do
or do not walk, especially influences that potentially fall within the remit of policy. Of those factors that can be
identified, walking behaviour appears to be most influenced by weather, gender and partnership status.
Nevertheless, the simple fact that the standard background characteristics account for so little of the variation in
walking behaviour, unlike the case for active participation in sport, is itself instructive. It implies that the likelihood
that people walk may well be governed by lifestyle, choice and environmental influences that are largely unrelated
to socio-economic standing. Future research might aim to identify such influences more precisely.
31
8. International Comparison
Highlights
• Active participation in sport and exercise in Ireland is broadly in line with participation in other developed
countries
• Participation rates are nevertheless far behind those of the best performing countries, which are the
Scandinavian nations and English-speaking Commonwealth nations
• Participation rates are clearly ahead of the worst performers, which tend to be Southern European nations
Introduction
It is natural to ask how Ireland compares with other countries in terms of participation in sport. However,
although this task appears straightforward, it is notoriously difficult to make accurate comparisons. In addition to
methodological differences in the collection of survey data across countries, there is no agreed definition of “sport”.
For instance, the European Commission has published results based on the Eurobarometer surveys (European
Commission, 2004), which suggest that Ireland has higher participation rates than the EU average, especially
Southern European nations, such as Spain, Greece and Italy, but lower than the leading countries, which are
Finland, Sweden and Denmark. Yet this survey simply asks people “How often do you exercise or play sport?”,
translated into each of the European languages, without in any way defining what counts as “exercise” or “sport”
and what does not. In particular, respondents are given no guidance as to whether recreational walking or
cycling should be included. The Eurobarometer reports that 53% of Irish adults exercise or play sport every
week. This is an unrealistically high figure for participation if walking is excluded, and an unrealistically low one
if it is included, suggesting that different people responded to the question in different ways. The results must
therefore be regarded as, at best, very approximate.
In searching for a better international comparison, the most robust estimate we could find comes from the
Carter Report in the UK (Carter et al., 2005), which employed a definition based on participation in all sport
or exercise, including walking, to a given level of intensity, for 30 minutes or more, three times a week. Carter’s
commission assembled information based on recent surveys for nine countries. Even so, the comparison
remains approximate, given the different survey methodologies, dates of fieldwork and linguistic idiosyncrasies
surrounding definitions.
Key Results
To make the comparison, a total of walks and sessions of sport was compiled from the ISM, in close accordance
with the definition employed by the Carter Report. The following criteria were applied. Walks over 29 minutes
by respondents who described their walking pace as either “Fairly Brisk” or “Fast” were counted as contributing
to the total. Sessions of sport of over 29 minutes involving enough effort to make them out of breath or sweat
were also counted.
The proportion of respondents whose combination of walks and sessions of sport was three or more was then
calculated and compared with data for the nine countries compiled by the Carter Report.
32
Figure 8.1: International comparison of participation in sport and exercise by adults
(proportion who participated in moderate to vigorous sport or exercise lasting at least 30
minutes on three days during the previous week)
Source: Carter et al. (2005) and ISM 2007
60
52
50
46
39
40
%
27
30
26
26
26
24
21
20
11
10
0
Finland
Australia
Canada
Germany
Ireland
Japan
USA
France
England
Italy
The results are presented in Figure 8.1. According to this comparison, Ireland is firmly in the middle of the
range, but well behind the leading nations for participation in sport and exercise. (Note that the figure of 26%
for Ireland is not comparable with the activity levels given in Chapter 2, because the comparison employed by
the Carter Report stipulates higher effort levels).
However, it is quite possible that the picture presented here is on the optimistic side regarding Ireland’s
participation rates. This is because the figures for other nations were all compiled from surveys conducted prior
to 2005, and mostly around 2002. If the pattern of increasing participation in Ireland identified by Lunn and
Layte (2008) is replicated in other countries, which given the common social forces involved is quite likely, the
figures may underestimate participation in the comparison countries by as much as several percentage points.
Discussion
The results presented in this chapter must be treated with caution. The comparison is imprecise, for the reasons
described in the introduction. However, for two reasons, the broad pattern contained in the results can be
considered to be indicative of the international picture. First, the differences in participation rates recorded
between some countries are very large. Second, the broad pattern produced by this comparison is consistent
with that indicated by the Eurobarometer findings.
Hence, the following conclusion may be drawn. Active participation in sport and exercise in Ireland appears
to be roughly in line with many other developed countries. Yet participation is clearly well behind the leading
countries, which tend to be the Scandinavian nations and English-speaking Commonwealth nations. It is also
well ahead of the backmarkers, which tend to be the Southern European nations.
33
Part Three:
Social Participation
34
9. Volunteering
Highlights
• 8% of adults had volunteered for sport-related activity in the previous 7 days, equivalent to 280,000
volunteers
• Disabled people who said they could not actively participate in sport were more likely to be involved as
volunteers than those without a disability
• The average time devoted to volunteering in the previous 7 days was two hours, but women and, especially,
men over 65 years of age devoted very much more time
Introduction
In addition to asking respondents about active participation in sport and recreational walking, the ISM
questionnaire also asks about the social side of sport, including voluntary activities associated with sport,
membership of clubs and attendance at sports events. This chapter examines patterns of volunteering.
Sport in Ireland is supported by significant amounts of voluntary activity. Without this work, which provides
transport, coaching, officiating and many other activities, it is likely that less sport would be played and that the
quality of the sporting experience would be diminished. The results show that levels of voluntary activity vary
significantly, both seasonally and across the population.
Key results
In 2007, 8% of people were involved in a voluntary
activity in the previous 7 days, equating to almost
280,000 people. This is less than the 15% reported
in Delaney and Fahey (2005) on the basis of the
2003 SSPE. The difference probably reflects the
longer reference period of 12 months employed in
the earlier survey, as opposed to 7 days in the ISM.
Reported volunteering was higher among men (10%)
than women (6%), a ratio similar to that previously
reported. There was also marked variation across
the year, as shown in Figure 9.1, with the proportion
volunteering peaking in the third quarter of the year.
It is likely that this peak reflects the course activity of
late summer, the beginning of the academic year (see
the effect of children below), plus the fact that autumn
is the start of the season for many sports.
Figure 9.1: Volunteering by gender and
season
12
10
8
%
6
4
2
0
Q1
Q2
Q3
Q4
Male
All
Female
35
Volunteering associated with sport is higher among
men across all age groups, with the largest difference
between men and women occurring for those aged 55 to
64 (Figure 9.2). Nevertheless, the pattern of volunteering
across the life course is similar for men and women. It
rises substantially after age 35, before falling away again
among older age groups. This patterning by age reflects
a number of processes, including the type of connection
that individuals have to sport.
Figure 9.2: Volunteering by age and gender
For example, the probability of volunteering is
enhanced by having a family member who participates
in sport. The pattern across age groups is strongly
related both to the likelihood of having children and
the age of those children, as can be seen from Figure
9.3. The proportion volunteering is always highest
among those with children, particularly children
under 18. Interestingly, older parents of younger
children may be more likely to volunteer than younger
parents, although the relationship falls short of
statistical significance.
Figure 9.3: Volunteering by age and
presence of children
There is an interesting relationship between
volunteering and disability. We might anticipate
that poor health and/or disability would be an
impediment, but it is also possible that being unable
to participate actively in sport may lead to higher
rates of volunteering if there is a strong desire to be
involved. Respondents were asked whether they have
any long-standing illness, health problem or disability
that limits daily activities or work. If so, they were also
asked whether this prevents them from taking part
in sport or exercise. Figure 9.4 shows that, above age
44 at least, those who have a health problem and are
prevented from active participation are more likely
to volunteer than those who are healthy. Interestingly
though, those with health problems, but who are not
prevented have a lower level of participation.
Figure 9.4: Volunteering by disability status
20
15
% 10
5
0
16-24
25-34
Male
Female
35-44
45-54
55-64
65+
25
20
%
15
10
5
0
No Children
35-44
Children <18
45-54
Children 18+
55-64
25
20
%
15
10
5
0
25-34
No disability
35-44
45-54
Disabled, prevented
55-64
65+
Disabled, possible
Note: Incidence of disability in youngest age group is too low to produce reliable figures
Previous research on volunteering associated with sport has shown that those with higher educational attainment
and income are more likely to have a voluntary involvement in sport, although the relationship between
volunteering and socio-economic factors is not as strong as that found for active participation (Lunn, 2007a).
36
Figure 9.5: Relative odds of volunteering by
household income (over 35s only)
1.4
1.2
Odds ratio
Figure 9.5 shows volunteering is moderately associated
with reported household income. The chart displays
the odds of volunteering, controlling for gender and
age, relative to the poorest income group (which
takes the value 1). As income increases, so does the
likelihood of volunteering. Analyses show, however,
that this relationship is not consistent with age. Up
to 35 years, it is actually reversed, with those of
lower income being more likely to volunteer. Hence,
the relationship depicted only applies after age 35.
Higher income groups may be less likely to find time
for volunteering as young adults, only beginning
involvement once they have children.
1
0.8
0.6
0.4
0.2
0
<�300
300-399
400-499
500-749
750-899
900-1249
�1250+
Figure 9.6 shows that volunteering is also associated
with educational attainment. More educated people
are more likely to volunteer, although the probability
for those with a third level qualification is somewhat
lower than for those with “Other 2nd level” (even
controlling for sex and age). These gradients for
income and educational attainment confirm previous
findings in the Irish context and also underline the
important relationship between disadvantage and
involvement in sport. One example of the way in
which economic advantage increases volunteering is
in ownership of a car. Those who have access to a car
are three times more likely to volunteer.
Figure 9.6: Volunteering by educational
attainment
The types of voluntary activities carried out over the
previous week varied widely (Figure 9.7). The most
common activity was coaching, which accounted for
34% of volunteering, followed by providing transport
(29%) and being a club official (21%). However, the
most common forms varied significantly by gender.
Men were much more likely to coach than women
(45% v 15%), while women were more likely to
provide transport (45% v 19%). Men are also more
likely to take on the position of club official, whereas
women are more likely to be activity organisers.
Figure 9.7: Types of volunteering by gender
Although our analyses so far show that men and
those in the 35 to 44 age group were more likely to do
voluntary activities related to sport, among those who
do volunteer, the average number of hours devoted
to it varies significantly. Of all volunteers, half do two
hours or less, but 5% report 21 or more hours in the
last week. Figure 9.8 shows average hours volunteered
by age and gender. Women who volunteer do over
one hour more than men who volunteer, although
the overall proportion of women volunteers is lower.
Meanwhile, men over 65 years are particularly likely
to devote a high number of hours to volunteering
Figure 9.8: Time devoted to volunteering by
gender and age
12
8
%
4
0
Primary
Junior
Cert
Leaving
Cert
Other 2nd
Level
Third
Level
Female
Male
Other
Referee
Mentor
Selector
Kit Maintenance
Activity Organiser
Club Official
Coach
Providing Transport
0
10
20
%
30
40
50
16
12
%
8
4
0
16-24
25-34
Male
Female
35-44
45-54
55-64
65+
Discussion
This chapter provides further evidence of the substantial voluntary activity associated with sport in Ireland. Our
results show that around 8% of adults volunteered during the previous 7 days, providing coaching, transport,
officials and organisation, among other functions. Although this level of volunteering represents a very
considerable contribution to Irish sport, comparing levels of volunteering with levels of active participation,
the present study falls some way short of the conclusion reached by Delaney and Fahey (2005), that there are
three volunteers for every four active participants who play with enough regularity and effort to derive physical
benefit. The difference reflects the different reference periods used for the SSPE survey and the ISM, implying
that volunteering is somewhat less regular than playing.
Volunteering is strongly related to the context of people’s lives. Having children increases the probability of
volunteering while children are of school-going age. After this, the difference between those with and without
children falls away. High educational attainment is associated with an increased probability of volunteering.
This may stem from the better educated having stronger links to sporting networks. Also, while higher
incomes are not essential to voluntary activity, it may help to have a car and to be able to contribute with one’s
own resources.
37
There are major gender differences in voluntary activities undertaken. To generalise, men tend to take official
roles, while women are more likely to carry out tasks that, while essential to the operation, entail less influence
over how sporting organisations are run. The data cannot determine what impact this gender divide has, nor
whether those involved perceive any unfairness in this distribution of voluntary labour. But it clearly raises
questions about the social position of women within sport.
The variation in time spent volunteering means that some people contribute to sport in a form equivalent to
an unpaid part-time job. On average, volunteers reported two hours of time spent volunteering, but 1 in 10
provided ten or more hours and 1 in 20 reported twentyone or more hours.
38
10. Club Membership
Highlights
• 32% of adults are members of sports clubs
• Disabled people over age 45 who said they could not actively participate in sport were more likely to be club
members than those without a disability
• Club membership was strongly related to high income and educational attainment
Introduction
Sports clubs are the scaffolding within which much sport and exercise in Ireland takes place, but clubs vary
dramatically in the extent to which they are market orientated (as say in the case of gyms) and formally
structured (e.g. a five-a-side soccer team versus a GAA club). This chapter examines the pattern of club
membership in 2007.
Key results
Overall, 32% of respondents report being a member
of a club or other organisation that provides an
opportunity to engage in physical activity for
recreation, exercise or sport. Figure 10.1 shows that
across all age groups men are more likely than women
to be a member of a club. The proportion who are a
member of a club is also highest in the youngest age
group at 47%, declining to 17% among those aged 65
or more. These figures are in close accordance with
previous findings (Delaney and Fahey, 2005).
Figure 10.1: Club membership by age and
gender
Figure 10.2 shows that there is seasonal variation
in club membership. It is highest for both men and
women at the beginning of the year, at 40% and 23%,
with the proportion falling in quarter 2 before rising
again in quarter 3. This variation largely reflects the
twin periods for joining clubs: the beginning of the
year for gyms and exercise, the autumn for team
sports such as GAA, soccer and rugby.
Figure 10.2: Club membership by season
and gender
70
60
50
%
40
30
20
10
0
16-24
25-34
Male
Female
35-44
45-54
55-64
65+
50
40
%
30
20
10
0
Q1
Q2
Q3
Q4
Male
All
Female
39
Figure 10.3 shows that whereas the probability of
club membership falls with age among those without
disability, it increases among those with a disability,
reaching a peak in the middle age groups before falling
thereafter. Above age 45, disabled people are actually
more likely to be members than the non-disabled.
This is similar to the pattern found for volunteering
and suggests that those unable to participate in sport
because of physical constraints are still active members
of the sporting community, albeit in another form.
Figure 10.3: Club membership by age and
disability
40
35
30
25
% 20
15
10
5
0
25-34
35-44
No disability
45-54
Disabled, prevented
55-64
65+
Disabled, possible
Previous research has shown that club membership is significantly influenced by socio-economic factors (Lunn,
2007a). This is unsurprising, since membership can often involve quite substantial fees, particularly in private
gyms, golf or tennis clubs. Those groups with less disposable income will be less likely to spend their limited
resources on memberships.
40
Figure 10.4 shows, as expected, that there is a simple
and graduated relationship between household income
and the probability of being a member of a sports
club. Those in the highest income group are over six
times more likely to be a member of a club than those
in the lowest income group. Analyses controlling for
education, employment status, age, sex and children
shows this strong relationship between income and
membership is robust.
Figure 10.4: Club membership by income
Figure 10.5 shows that club membership is also quite
strongly related to educational attainment. Those
with higher levels of education are significantly more
likely to be a club member. Analyses show that even if
we control for the individual’s level of income, those
with higher levels of education are still more likely
to be a member of a club. Hence, differences across
educational groups do not appear to be due to income
differences alone. Lunn and Layte (2008) show that
the sporting opportunities enjoyed by those who
remain in education can have lasting effects on later
participation, probably including the likelihood of
club membership.
Figure 10.5: Club membership by
educational attainment
60
50
40
%
30
20
10
0
<�300
300-399
400-499
500-749
750-899
900-1249
�1250+
50
40
%
30
20
10
0
Primary
Junior
Cert
Leaving
Cert
Other 2nd
Level
Third
Level
One of the main determinants of an individual’s level
of income is their job. Thus, it is unsurprising that
an individual’s occupational class is also a very good
predictor of whether they will be a member of a club.
Those who are employed or self-employed have a
high probability whereas those who are unemployed
do not. However, this effect is not simply a function
of income differences between the employed and
unemployed. Even controlling for income, being
employed seems to increase the probability of being a
member. It may be that being employed offers access
to social networks, which may increase the likelihood
of being a member of a club. Another interpretation
is that those who are working require the structured
opportunity to exercise which gyms and clubs offer.
The availability of time also plays a role in club
membership. Analysis of membership by employment
status also reveals that the retired are more likely than
the employed to be club members.
Figure 10.6: Number of club memberships
by gender
Males
Three or more 5%
Two 21%
One 74%
Females
Three or more 2%
Two 11%
One 87%
Many individuals are members of more than one club, as shown by Figure 10.6. Over 25% of men have two or
more club memberships. Analysis shows that the number of memberships held also increases with income, but
only up to the middle income groups.
Discussion
Sports club membership is an important element in the institutional structure of sports participation in Ireland.
This chapter shows that almost one-third of the population aged 16 and over are members of a sports club. This
proportion masks overall variation within the population, however, since almost half of those under the age of
24 report being a member of a club, a proportion which falls to 17% among those aged 65 or more.
As with sports participation or volunteering, club membership is also more common among men, with the
biggest gap in membership between the sexes appearing in the youngest age group. The results here also
underline the importance of socio-economic factors in shaping club membership with income, education and
employment status all important determinants.
41
11. Attendance
Highlights
• 17% of adults had attended a sporting event in the previous 7 days
• Men were more likely to attend than women, but women with children under 18 were particularly likely to
attend and more likely to attend two or three events
• Attendance was strongly affected by income and social class
Introduction
The ISM survey asks about attendance at any sporting fixtures or events in the previous 7 days, as a spectator or
supporter (rather than as an active participant). While attendance is strongly influenced by age, with younger
age groups more likely to attend, parents in middle age groups have particularly high rates of attendance,
presumably to watch their children.
Key results
Some 17% of adults had attended an event during the
previous 7 days. Figure 11.1 reveals some seasonal
variation. Attendance increased from 15% in the first
quarter to 21% in the third quarter, before falling
back at the end of the year. The peak coincides with
the beginning of the season for many team sports.
The seasonal profile varies by gender, suggesting
that the kinds of events attended by men and women
were different. The narrowing of the gender gap in
the second quarter may reflect the greater popularity
among men of traditional team games, which are least
likely to be played at that time.
Figure 11.1: Attendance at a sporting
fixture by season
Figure 11.2 shows that men were more likely to attend
an event than women (20% versus 12% overall).
Analysis by age group shows that the youngest age
group are significantly more likely to attend an event
(32% of men and 16% of women). For men the pattern
as age rises is fairly flat at around 20% until the oldest
age group among whom less than 10% attended in the
last 7 days. These findings are consistent with previous
research (Delaney and Fahey, 2005).
Figure 11.2: Attendance by age and gender
30
25
20
% 15
10
5
Male
Female
All
0
Q1
Q2
Q3
Q4
40
30
% 20
10
0
16-24
25-34
Male
Female
35-44
45-54
55-64
65+
This pattern for men is confirmed by multivariate models controlling for a large number of other factors. These
show that those older than 25 are around half as likely to attend an event as the youngest age group and those in
the oldest age group 40% as likely.
42
For women the pattern is more complex, with those
aged 35 to 44 more likely than either older or younger
age groups to attend. Multivariate analysis shows
that this pattern reflects the likelihood of having
children under 18 years. Figure 11.3 shows this
effect, by providing figures separately for women
with and without children under 18 years. For the
latter, attendance peaks in the youngest age group
and decreases thereafter. For those with children,
attendance peaks in the 35 to 44 age group, before
decreasing thereafter. (Women with children over the
age of 18 have an attendance pattern similar to women
with no children). There is a somewhat similar though
less striking pattern among men, with the peak for
those with children under 18 years between 45 and 55.
Figure 11.3: Women’s attendance by
presence of children under 18
Previous research on attendance has shown significant
differences in the frequency of attendance by
educational attainment, with more education being
associated with higher levels of attendance (Lunn,
2007a). Figure 11.4 shows that the ISM data reveal a
different effect. People with leaving certificate level
education are more likely to have attended a fixture
in the previous 7 days than those with a third-level
qualification (or another second level qualification).
Figure 11.4: Attendance by educational
attainment
25
20
15
%
10
5
0
16-24
25-34
No Children
35-44
45-54
55-64
Children Under 18
25
20
15
%
10
5
0
Primary
Junior
Cert
Leaving
Cert
Other 2nd
Level
Third
Level
Again, this difference may well be due to the difference in reference period (12 months versus 7 days). It could
be that people with higher educational attainment attend fixtures less frequently, but that a higher proportion
would attend at least once over a longer period. It is difficult to test this theory directly. Another plausible
explanation concerns the interactions of age, education and social class. Multivariate analysis suggests that in the
youngest age group, lower educational attainment may increase attendance, because many of those not in higher
education have jobs and thus higher personal incomes also. As age increases, however, this effect disappears. Yet
patterning by social class also contributes. Farmers, self-employed and other non-manual class groups are likely
to have leaving certificate qualifications and also have relatively high rates of attendance. Interestingly, women in
the farming category have particularly high rates of attendance. Indeed, once we control for age and social class,
differences across the educational attainment groups are no longer statistically significant.
Figure 11.5 shows that, as with volunteering and
membership of sports clubs, attendance at a sporting
event is strongly influenced by the income level of the
individual involved. Higher income is associated with
higher attendance, although Figure 11.5 shows that
the relationship is not entirely simple. The probability
of attendance does increase with income, but peaks in
the second highest category before decreasing in the
highest. This pattern remains even after controlling
for a large number of other variables
Figure 11.5: Attendance by income
25
20
%
15
10
5
0
<�300
300-399
400-499
500-749
750-899
900-1249
�1250+
43
There are also some other significant determinants
of having recently attended a sporting event.
Disability has important consequences for patterns
of attendance. As found in club membership and
voluntary activity in sport, those with a disability
that discounts them from active participation were
actually more likely to have attended a sporting event
than those without a disability. However, those with a
disability but who perceive that they are not prevented
from participating in sport were less likely than the
able bodied to have attended a fixture. Once again,
this suggests a disability that prevents participation
in sport actually increases the probability of trying
to find another form of sporting involvement such
as attendance. Car ownership also emerges as an
important factor. As found for voluntary activity,
those with a car or access to a car were almost twice as
likely to have attended an event in the last 7 days than
people without a car
Figure 11.6: Number of events attended by
gender
Males
Three or more 5%
Two 15%
One 80%
Females
Three or more 8%
Two 19%
One 73%
Almost one-quarter of those who had attended an event in the previous 7 days had attended more than one
(Figure 11.6). Interestingly, women attendees were more likely to have attended two or more events than their
male counterparts. Analysis shows that this difference reflects the attendance of mothers of children under 18 at
children’s sporting events.
Discussion
The results presented in this chapter show that attendance at sporting events is far from being a random process,
but is strongly influenced by factors such as age, gender, presence of children and socio-economic factors such
as education and income.
The findings are in keeping with previous research, which has shown that the type of event attended and
specifically whether it involves adult or child participants is an important determinant of the patterns observed.
In the present case, parents of children aged under 18 were far more likely to attend sporting events than others
their age without children under 18 and, indeed, more likely than much younger age groups who have higher
rates of attendance overall.
The findings also confirm that attendance at sports events in Ireland is highly structured by socio-economic
factors such as income and education. However, our results suggest that the reference period is crucial, as those
with third level qualifications attend less frequently, but are more likely to do so at least once over a longer period.
44
Part Four:
Conclusions
45
12. Contribution of the 2007 ISM
With its combination of large sample-size and sole focus on sporting activity, the Irish Sports Monitor is
designed to provide the most accurate account of adult grassroots Irish sport available to date. The results
contained in the previous chapters therefore offer improved benchmarks for future comparison. The more
detailed findings reinforce some of the main messages of previous research, but also add some new insights.
Thus, Irish sports policy now has available to it a substantial body of evidence.
Benchmarks
The classification of the population into four categories of physical activity, in Chapter 2, combines individual
data on walking and on playing sport. Separate headline figures for participation in each of these components
are given in the same chapter. These figures provide benchmarks against which developments in levels of
physical activity and in walking and playing sport may be judged.
In addition to these headline numbers, the 2007 ISM provides baseline data for the frequency, duration,
intensity and context of sporting activity (Chapter 3), levels of participation by different social groups (Chapter
4) and by area (Chapter 5), detailed levels of walking activity (Chapter 7), headline participation rates for
volunteering (Chapter 9), club membership (Chapter 10) and attendance at sporting events (Chapter 11). These
findings permit the evolution of Irish sport to be accurately monitored in coming years.
Reinforcement of previous findings
There is now considerable consistency in the available data relating to grassroots Irish sport, which allows solid
conclusions to be formed.
Looking across the 2003 SSPE, the 2006 QNHS and the 2007 ISM, a clear picture emerges of the amount and
type of sporting activity in Ireland. Most people walk regularly: 58% for at least twenty minutes a week. A
substantial minority of the adult population actively participates in regular sport and exercise: 33% according to
the criteria and definition of participation used here. These numbers are in line with previous findings.
Compared to non-participants, active participants are, on average, better educated, more likely to be male,
younger and richer. Combining the effects of educational attainment, income and social class, there is a very
strong socio-economic bias in sporting activity.
There is also a consistent picture regarding the popularity of sporting activities. Personal exercise activity
(going to the gym, using exercise machines, taking fitness/aerobics classes) is the most popular form of sport
and exercise in Ireland. Swimming, soccer and golf are the only other sports in which more than one in twenty
adults participate regularly.
Walking is an extremely important form of adult exercise, since it accounts for a very large amount of physical
activity and is the only type of regular physical activity for many people.
In addition to active participation, i.e. playing sport, there are a substantial number of people who engage with
sport as social participants; as volunteers for sport-related activity, spectators at sporting fixtures and members
of sports clubs.
46
New findings
The more accurate 7 day reference period used by the ISM, with year-round collection, plus a more detailed
set of questions regarding the precise nature of people’s involvement compared to previous questionnaires, has
produced some new findings.
The rise of personal exercise activities is not confined to active participation, but extends to club membership
as well. Gym and fitness/health club membership is now the most frequent form of sports club membership,
overtaking membership of GAA clubs.
There was substantial seasonal variation in activity. Active participation dropped during the latter part of the year.
Summarising the seasonal effects across all forms of participation, including the social forms, the third quarter of
the year sees substantial pick-up in sporting activity. This is very likely to be linked to the beginning of seasons
and the start of the academic year. Later years will be able to confirm whether this seasonal pattern is regular.
The majority of active participation in sport takes place in a non-organised context, with over one-quarter being
undertaken by people on their own. The most common context (35%) for playing sport is with friends and family.
Previous research has shown the strong associations between playing sport, educational attainment and
income. The present survey suggests that the impact of income may be even greater than previously reported.
Furthermore, even controlling for educational attainment and income, those of lower social class (as determined
by occupation) are less likely to play sport.
There is a link between nationality and playing sport: nationals from non-English-speaking countries and nonEU countries are less likely to play sport.
The sample-size of the ISM allowed investigation of participation rates by county (or council in greater Dublin).
There are considerable differences in participation rates in different areas, with some counties outperforming
others by statistically significant amounts, even after controlling for demographic factors.
International comparison would suggest that Ireland’s performance in terms of grassroots participation in sport
is middling. We lag behind the Scandinavian nations and English-speaking Commonwealth nations, but are
ahead of the worst performers, which tend to be the Southern European nations.
Based on the 7 day reference period used here, the ratio of players to volunteers in sport is perhaps not as great
as was previously thought – some 8% had volunteered in the previous 7 days, meaning that sport has one weekly
volunteer for every four weekly participants. Nevertheless, looking at the range of activities they perform and
the hours they devote, volunteers are an essential component of Irish sport.
47
The ISM and sports policy architecture
Five previous ESRI reports have detailed more than forty specific policy implications relating to quantitative
research since 2004, including more than thirty that relate to adult sport. This first ISM Annual Report for
2007 reinforces the empirical basis from which those implications were derived. Although there are some
minor differences in findings and emphasis, the picture is overwhelmingly one of consistency between different
surveys and studies.
This is pleasing from the point of view of the reliability and quality of the evidence base. We know where we stand.
The ongoing role of the ISM is now to monitor levels of participation into the future; to see whether the
combination of social forces, individual decisions and policy efforts that drive people to get actively involved in
sport will deliver higher levels of participation, in line with the aims of policy. Yet, at the same time, the findings
have the capacity to contribute to our understanding of those same forces, decisions and policies, such that we can
better understand why people participate and can better design policies to encourage and assist them to do so.
In this sense, the ISM, as described in the introduction, can become part of the policy architecture. Whether it
does so will depend on the quality of the evidence it produces and the inclination and ability of policy makers to
employ that evidence to good effect.
48
References
Carter, P. 2005. “Review of National Sport Effort and Resources”, Report for HM Treasury London, UK:
Department of Culture, Media and Sport.
Central Statistics Office 2007. “Quarterly National Household Survey: Sport and physical exercise” Cork:
Central Statistics Office, Ireland.
Delaney, L. & Fahey, T. 2005. Social and Economic Value of Sport in Ireland Dublin: Economic and Social
Research Institute.
European Commission 2004. “The Citizens of the European Union and Sport”, Special Eurobarometer 213.
Fahey, T., Layte, R., & Gannon, B. 2004. Sports Participation and Health Among Adults in Ireland Dublin:
Economic and Social Research Institute.
Fahey, T., Delaney, L., & Gannon, B. 2005. School Children and Sport in Ireland Dublin: Economic and Social
Research Institute.
Lunn, P. 2007a. Fair Play? Sport and Social Disadvantage in Ireland Dublin: Economic and Social Research
Institute.
Lunn, P. 2007b. “Ballpark Figures: Key research for Irish Sports Policy” Dublin: Irish Sports Council.
Lunn, P. & Layte, R. 2008. Sporting Lives: An Analysis of a Lifetime of Irish Sport Dublin: Economic and Social
Research Institute.
World Health Organisation 2003. “Health and Development Through Physical Activity” Geneva: World
Health Organisation.
49
Appendices
50
Appendix A - ISM Technical Report
Sampling
The 2007 Irish Sports Monitor was conducted by telephone with over 10,000 adults (age 16 and over) in 2007.
Interviewing took place in 440 randomly selected sampling points throughout the country between February
and December 2007.
The ISM employs a three-stage clustered sampling design. The first stage is the selection of the Primary Sampling
Unit from the GeoDirectory – a listing of all addresses in Ireland. The sampling points are based on aggregates of
town lands. The second stage is the selection of the household within each of the 440 sampling units selected at
the first stage. For each cluster, one or more sets of 100 telephone numbers are randomly generated. Not all of the
numbers generated are actually live numbers to private households. Some will not be valid numbers; some will
be to businesses; some will be valid numbers to households which have no persons whose principal status is “at
work” and so on. This means that there is quite a degree of ‘wastage’ in the telephone numbers generated in each
Primary Sampling Unit. This ‘wastage’ does not adversely impact on the statistical nature of the resultant sample.
The third stage is the selection of the actual individual within the household who will fill out the questionnaire. We
impose a post-stratification selection rule in the selection of the individual within the household chosen for interview.
This is based on gender, economic status (at work or not at work) and broad age group (under 45 and age 45 or over).
This is done to ensure a representative mix of males and females and different age groups. If this post-stratification
selection criterion were not imposed, females over 45 years of age would be over-represented in the final sample for
analysis, since willingness to participate in surveys is highest among this group in almost all surveys undertaken.
Sample size and response rates
The survey is conducted by ESRI interviewers, on a telephone basis, with the respondent in his/her home.
Interviewers are instructed to attempt each number four times before recording a ‘non contact’, ensuring that at
least two of the calls are on different weekday evenings and at least one was at the weekend.
Table A1 outlines the response rates to the survey in 2007. A total of 61,394 numbers were called, resulting in a
total of 9,767 fully completed and usable questionnaires; a further 250 partially completed forms which were not
used in the analysis; a total of 9,137 households where the household refused to participate in the survey. There
were 1,652 households where potential respondents were excluded because of the post-stratification controls
(see above), 16,129 where there was consistently no reply, 5,857 were business numbers and 18,602 numbers
were not in service. Excluding the ineligible households we made contact with a total of 19,154 valid households.
Fully completed and usable questionnaires were completed with 9,767 of these households. This gave an effective
response rate of 51 per cent of the valid sample, or 35 per cent if we assume that 42 per cent of the non-contacts are
eligible (derived from the fact that 42 per cent of the calls where eligibility is known were to eligible households).
Table A1: Survey Response Outcomes
Number of
Cases
Per cent
of valid
numbers
Per cent including noncontacts with adjustment
for percentage eligible
Completed
Partially completed
Refused
Total Valid Calls
9,767
250
9,137
19,154
51%
1%
48%
100%
35%
1%
33%
(27,631)
Out of quota
Consistent no reply
Business Number
Non-existent
1,652
16,129
5,857
18,602
–
–
–
–
Total
61,394
51
The Questionnaire
During the interview, the ISM questionnaire (supplied in Appendix B) begins after a series of questions about
the state of the economy, which are used to compile a consumer sentiment index. This feature is part of the
initial design of the ISM. It has the advantage that the interview is not solely directed at sport and is not initially
described to an individual who receives a call as being a survey about sport. This effectively removes the
possibility that those not interested in sport might simply refuse to take part, thereby biasing the sample. Once
respondents have agreed to do a survey, it is very rare that they pull out part way through.
The questionnaire is organised into 3 main sections. Section A records details on the respondent’s participation
in sport, either as a player, volunteer, club member or spectator. Section B is designed as a flexible module
of questions. It is intended that this module will be changed at least once during the year’s data collection,
allowing ongoing opportunities to address new research questions with large-sample data. Analyses of Section B
questions are not included in the present report. Section C records some additional background information on
the respondent not already recorded during the economic questions that preceded the sport questions.
Reweighting the data
The purpose of sample weighting is to compensate for any biases in the distribution of characteristics in the
completed survey sample compared to the population of interest, whether such biases are due to sampling
error, to the nature of the sampling frame used, or to differential response rates. Whatever the source of the
discrepancy between the sample and population distributions, we would like to adjust the distributional
characteristics of the sample in terms of factors such as age, sex, economic status and so on to match that of the
population. As with most surveys, the completed sample for the ISM under-represented ‘hard to reach’ groups
such as young adults, males and those at work, and sample weights are needed to ensure that point estimates
from the data represent the population as a whole.
In the current survey this was implemented using a standard statistical technique known as calibration which
involves comparing sample distributions to external population figures, in this case derived from the Quarterly
National Household Survey (QNHS). The QNHS is based on interviews conducted in over 33,000 households
each quarter. The data used came from the first to fourth quarters 2007. The figures from the QNHS followed
revisions arising from Census 2006.
The variables used in the weighting scheme were:
•
•
•
•
•
•
Age cohort (9 categories) by gender
Level of educational attainment (4 categories) by gender
Principal economic status (6 categories) by gender.
Marital status (4 categories) by gender by age group (2 age groups for single adults, 3 age groups for married adults).
Region (3 categories)
Number of persons age 16 and over in the household (special figures provided by the CSO, 5 categories)
The weighting procedure involved constructing weights so that the distribution of each of the characteristics for
the responding individuals was equal to the distribution of these characteristics for the population of persons
age 16 and over. Weighting was accomplished by using a minimum distance algorithm, which adjusts the
marginal distributions for a number of variables simultaneously using an iterative procedure.
As the completed sample size differed appreciably by quarter, the weights were separately constructed within
each quarter, and an annual weight was constructed by taking the average across quarters. Using the annual
weight, the weighted sample is representative of the population age 16 and over living in private households in
2007. The quarter-specific weights are needed to produce figures for each quarter. The weights were constructed
so as to gross the results to the population size.
52
Appendix B Questionnaire
Now I would like to ask you a few questions on recreation, exercise and sport. These questions are being asked on
behalf of the Irish Sports Council, but they relate to a broad range of physical activities as well as traditional sports,
including walking, cycling, other outdoor pursuits, water sports, and non-competitive or recreational exercise.
A1. First, I would like to ask you about any recreational walking you did in the last 7 days.
DO NOT include walks for transport, such as walking to work or to the shops, but DO include walks
undertaken for exercise, recreation or leisure.
In the last 7 days, did you take such a walk?
Yes c 1 No c
2 go to A5
A2. How many walks for exercise, recreation or leisure did you take? ________
A3. Approximately how many minutes did each walk last?
a. ____ b. ____ c. ____ d. ____ e. ____ f. ____ g. ____
[INT: If interviewee took more than 7 walks, please record the 7 longest]
A4. How would you describe your usual walking pace during this(these) walk(s)? [Tick ONE only]
Slow c 1 Steady, average c 2 Fairly Brisk c 3 Fast c 4 Don’t know c 5
A5. I would now like to ask you about any OTHER physical activities you undertook in the past 7 days for
exercise, recreation or sport.
Please DO NOT include physical activity for work, transport, or domestic work like gardening or DIY.
Please DO include personal exercise, such as swimming, dancing or jogging, as well as all forms of
sporting activity, indoor or outdoor, whether undertaken in an organised setting or casually with family
or friends.
So, in the past 7 days, did you participate in any such activities?
Yes c 1 No c
2 go to A22
A6. Please list up to 3 sports or activities, in the order in which you participated the most:
[INT: If answer includes any of the 6 sports in the table, it is ESSENTIAL to ask the relevant
follow-up question and record exactly which type of sport, as shown. Treat each of these as a
separate activity.]
A6a. __________________________
A6b. __________________________
A6c. __________________________
FOOTBALL
GOLF
RUNNING
CYCLING
BOWLING
HORSE-RIDING
Is that: GAA OR Soccer OR Five-a-side?
Is that: 18-hole OR Pitch & putt?
Is that: Athletics OR Cross-country OR Jogging?
Is that: Leisure OR Sport (Road, Mountain etc.)?
Is that: Ten-pin OR Lawn OR Road?
Is that: Leisure OR Sport (Show-jump, Racing etc.)?
53
I’d like to ask you a short series of questions about each activity, starting with the first
[INT: prompt activity A6a]
A7. On how many of the last 7 days did you take part? __________
A8. For how long did you take part? Consider a usual session if you took part more than once. _______
minutes
A9. Was the effort enough to raise your breathing rate? Yes c 1 No c
2
A10. Was the effort enough for you to be out of breath or sweat? Yes c 1 No c
2
A11. In what context did the activity take place? [Tick all that apply]
Organised training/
coaching/lesson
c1
Organised
competition
c2
Casually with family
or friends
c3
On own
c4
Other
c5
[INT: If no second activity (A6b) go to A22, else go to A12]
I’d like to ask you the same series of questions about the second activity… [INT: prompt activity A6b]
A12. On how many of the last 7 days did you take part? __________
A13. For how long did you take part? Consider a usual session if you took part more than once. _________
minutes
A14. Was the effort enough to raise your breathing rate? Yes…… 1 No……… 2
A15. Was the effort enough for you to be out of breath or sweat? Yes…… 1 No……… 2
A16. In what context did the activity take place? [Tick all that apply]
Organised training/
coaching/lesson
c1
Organised
competition
c2
Casually with family
or friends
c3
On own
c4
Other
c5
[INT: If no third activity (A6c) go to A22, else go to A17]
I’d like to ask you the same series of questions about the third activity
[INT: prompt activity A6c]
A17. On how many of the last 7 days did you take part? __________
A18. For how long did you take part? Consider a usual session if you took part more than once. _________
minutes
A19. Was the effort enough to raise your breathing rate? Yes…… 1 No……… 2
A20. Was the effort enough for you to be out of breath or sweat? Yes…… 1 No……… 2
54
A21. In what context did the activity take place? [Tick all that apply]
Organised training/
coaching/lesson
c1
Organised
competition
c2
Casually with family
or friends
c3
On own
c4
Other
c5
A22. I would now like to ask you about any voluntary activity associated with sport and exercise activities that
you undertook in the past 7 days. Voluntary activity means any role you may have fulfilled in support of
sport or recreational physical activity, for adults or children. It includes helping to run events, providing
or maintaining transport, food, equipment or kit, or acting in any kind of official capacity in relation to
an event, team or organisation that provides opportunities to engage in physical activities for recreation,
exercise or sport.
So, in the past 7 days, were you involved in any volunteering of this type?
Yes c 1 No c
2 go to A28
A23. What were the sports or physical activities concerned (up to a maximum of 2 you were most involved in)?
[INT: If answer includes any of the 6 sports in the table, it is ESSENTIAL to ask the relevant
follow-up question]
A23a. _________________________
A23b. _________________________
FOOTBALL
GOLF
RUNNING
CYCLING
BOWLING
HORSE-RIDING
Is that: GAA OR Soccer OR Five-a-side?
Is that: 18-hole OR Pitch & putt?
Is that: Athletics OR Cross-country OR Jogging?
Is that: Leisure OR Sport (Road, Mountain etc.)?
Is that: Ten-pin OR Lawn OR Road?
Is that: Leisure OR Sport (Show-jump, Racing etc.)?
A24. For sport … [INT: prompt activity A23a], what voluntary involvement did you have? [Tick all that apply]
Providing Coach Club
Activity
Kit
Selector
Transport
official Organiser Maintenance
c1
c2
c3
c4
c5
c6
Mentor
c7
Referee Other
(please
specify)
c8
c9
A25. How much time during the past 7 days did you devote to volunteering for this activity? ____________ hours
[INT: If no second activity (A23b) go to A28, else go to A26]
A26. For sport … [INT: prompt activity A23b], what voluntary involvement did you have? [Tick all that apply]
Providing Coach Club
Activity
Kit
Selector
Transport
official Organiser Maintenance
c1
c2
c3
c4
c5
c6
Mentor
c7
Referee Other
(please
specify)
c8
c9
A27. How much time during the past 7 days did you devote to volunteering for this activity? ____________ hours
55
A28 Are you a member of any kind of sports club? Include clubs for traditional sports, but also walking,
cycling or swimming clubs, fitness centres, gyms or other organisations that provide opportunities to
engage in physical activity for recreation, exercise or sport?
Yes c 1 No c
2 go to A31
A29. How many are you a member of? __________
A30. What are the sports or physical activities concerned (up to a maximum of 3 you are most involved in)?
[INT: If answer includes any of the 6 sports in the table, it is ESSENTIAL to ask the relevant
follow-up question]
A30a.______________________
A30b.______________________
A30c. ______________________
FOOTBALL
GOLF
RUNNING
CYCLING
BOWLING
HORSE-RIDING
Is that: GAA OR Soccer OR Five-a-side?
Is that: 18-hole OR Pitch & putt?
Is that: Athletics OR Cross-country OR Jogging?
Is that: Leisure OR Sport (Road, Mountain etc.)?
Is that: Ten-pin OR Lawn OR Road?
Is that: Leisure OR Sport (Show-jump, Racing etc.)?
A31. Given the broad definition of sporting activities we have been using, have you attended any fixtures or
events in the past 7 days, either children’s or adult events, as a spectator or supporter, rather than as an
active participant?
Yes c 1 No c
2 go to A34
A32. How many events did you attend? __________
A33. What were the sports or physical activities concerned (up to a maximum of 3 most recent events)?
[INT: If answer includes any of the 6 sports in the table, it is ESSENTIAL to ask the relevant
follow-up question]
A33a. ______________________
A33b. ______________________
A33c. ______________________
FOOTBALL
GOLF
RUNNING
CYCLING
BOWLING
HORSE-RIDING
Is that: GAA OR Soccer OR Five-a-side?
Is that: 18-hole OR Pitch & putt?
Is that: Athletics OR Cross-country OR Jogging?
Is that: Leisure OR Sport (Road, Mountain etc.)?
Is that: Ten-pin OR Lawn OR Road?
Is that: Leisure OR Sport (Show-jump, Racing etc.)?
A34. Apart from during PE lessons, did you play regular sport at school? Yes c 1 No c
2
A35. When you were at school, did your parents play any kind of sport regularly? [Tick ONE only]
Yes, both c 1 Yes, father only c 2 Yes, mother only c 3 No c 4 Don’t Know c
5
A36. Do you undertake any regular walks of over 15 minutes for transport, such as walking to work, walking
children to school etc.? By regular I mean at least once-a-week. Yes c 1 No c 2
A37. Do you cycle regularly as a form of transport? By regular I again mean once-a-week. Yes c 1 No c 2
**** Section B (Flexible Module) Inserted Here ****
56
Finally, I would like to ask you a few more background questions.
C1.
Do you have any long-term illness, health problem or disability that limits your daily activities or work?
Yes c 1 No c
C2.
Does this prevent you from taking part in sport and exercise? Yes c 1 No c
2
C3. Do you have any children? Yes c 1 No c
2
2 go to C6
C4. How many children do you have? ________
C5. What age is your youngest child? ________
C6. Does your household have a car? Yes c 1 No c
2
C7. Which of the following best describes where you live? [Tick ONE only]
In a city c 1 In a town c 2 In a village c 3 Isolated location c 4 Don’t Know c 5
C8. Which county do you live in? ______________ [INT: If TIPPERARY, specify North or South]
[INT: If DUBLIN go to C9, else got to C10]
C9.
Which of the following is your local authority?
Dublin City c 1 Dun Laoghaire-Rathdown c 2 Fingal c 3 South Dublin c
4
C10. What nationality are you? If joint nationality, please state both nationalities _______________________
[INT: Check Q22 in Consumer Survey – Is respondent the main earner in the household?]
Yes c 1 go to C11
No c 1 go to C13
C11. Do you supervise or manage anyone in your job?
Yes c 1 go to C12
No c 1 go to END
C12. Do you supervise or manage… Less than 25 people c 1 25 or more people c 2 These last two questions refer to the main earner in your household.
C13. Does he/she supervise or manage anyone in their job? Yes c
No c
1 go to C14
1 go to END
C14. Do he/she supervise or manage? Less than 25 people c 1 25 or more people c
2
THANK YOU VERY MUCH FOR TAKING THE TIME TO TAKE PART IN THIS SURVEY
INT: Gender of respondent: ________ Time interview ended ___ ___ : ___ ___ (24-hour clock)
57
Appendix C - Multivariate Model of Playing Sport
Logistic regression for determinants of being a “player”, as defined in Chapter 2.
Explanatory Variable
s.e.
p-value
(Wald)
Odds
ratio
Intercept
-.802
.195
.000
.448
Educational attainment
(Lower second level)
Primary
Higher second level
Other second level
Third level
Current student
-.169
.299
.249
.536
1.012
.114
.089
.131
.093
.140
.138
.001
.057
.000
.000
.845
1.349
1.283
1.709
2.752
Weekly income (€500 – 749))
Under €300
€300 - 399
€400 - 499
€750 - 899
€900 - 1249
Above €1250
-.177
-.182
.226
.033
.238
.575
.155
.132
.107
.086
.087
.085
.253
.167
.034
.700
.006
.000
.838
.833
1.254
1.034
1.269
1.778
.740
.059
.000
2.096
Age/10
-.289
.033
.000
.749
Employment status (Employee)
Retired
Not working
Home duties
.454
-.324
.277
.124
.149
.096
.000
.029
.004
1.575
.723
1.319
Occupational class (Skilled manual)
Professional/Manager
Non-manual
Self-employed
Farmer
Unskilled manual
No occupation
.046
.150
-.036
-.384
-.219
-.036
.086
.088
.081
.118
.130
.137
.592
.089
.656
.001
.092
.795
1.047
1.162
.965
.681
.803
.965
Disabled
-.550
.097
.000
.577
Children (No children)
Over 18
Youngest aged 10 to 18
Youngest under 10
.045
.047
-.228
.105
.100
.070
.667
.639
.001
1.046
1.048
.796
.534
.100
.000
1.706
.089
-.075
-.059
.069
.088
.072
.197
.393
.415
1.093
.928
.943
-.151
-.168
-.295
-1.194
.161
.191
.296
.246
.349
.379
.320
.000
.860
.846
.745
.303
Male
Access to car
Location
Town
Village
Isolated
Nationality
British
Other EU
Other English-speaking
Rest of World
N
Nagelkerke R-Squared
58
β
8,389
0.221
59
design_www.reddog.ie
Top Floor, Block A,
West End Office Park,
Blanchardstown, Dublin 15
T: +353 (0)1 860 8800
F: +353 (0)1 860 8880
E: [email protected]
www.irishsportscouncil.ie
60